Anthropic

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Technical Program Manager for Product, you'll drive the programs that bring Anthropic’s AI capabilities to the world. You’ll work closely with research teams to understand new model capabilities, then orchestrate across engineering, product, infrastructure, and go-to-market teams to ensure we launch reliably and at pace. This role is essential in orchestrating the cross-functional effort required to launch successfully as Anthropic continues to scale. This role offers unique challenges in coordinating high-stakes technical programs while maintaining the quality and reliability our customers expect. This position requires deep technical fluency, the ability to earn trust with researchers and engineers, and a talent for driving alignment across teams with different priorities and working styles. Responsibilities - Lead end-to-end program management for model and product launches, coordinating between research, engineering, product, infrastructure, and partnership teams - Drive cross-functional alignment and decision-making across workstreams, ensuring teams are unblocked and launches stay on track - Partner closely with Research PMs and engineering leads to sequence work, manage dependencies, and navigate technical tradeoffs - Track and communicate program status, risks, and dependencies to leadership and stakeholders - Build strong relationships with technical stakeholders, earning trust through deep engagement with the details - Coordinate with research teams to understand upcoming model capabilities and prepare launch plans accordingly - Navigate tradeoffs between speed, quality, and scope, helping teams make informed decisions under pressure - Develop and improve launch processes, playbooks, and operational frameworks that scale with our growing complexity - Create and maintain documentation of launch processes, decision logs, and cross-functional dependencies You may be a good fit if you - Have several years of experience in technical program management, with a track record of successfully delivering complex, cross-functional programs - Possess deep technical knowledge that allows you to engage meaningfully with ML researchers and engineers - Have experience managing programs with significant external dependencies and multiple stakeholder groups - Excel at translating between technical teams and stakeholders, making complex tradeoffs understandable - Can thrive in ambiguous situations, bringing structure to complex technical challenges - Have strong organizational skills and can manage multiple parallel workstreams effectively - Are comfortable operating at a fast pace where priorities shift and new challenges emerge quickly - Have excellent written and verbal communication skills, with the ability to influence without authority - Build trust quickly and maintain strong relationships even under pressure - Are passionate about Anthropic's miss

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Global Workplace & Real Estate team is delivering a rapidly expanding global portfolio — including full-building offices at the scale of ~450,000 SF that combine commercial kitchens, executive briefing centers and event space, high-end amenities, and the elevated power, cooling, and security infrastructure our work requires. We're hiring a Real Estate Construction Manager to lead the technical delivery of these projects from pre-construction through closeout and to serve as our primary technical counterpart to general contractors, design teams, and specialty vendors. This is a hands-on construction leadership role, not a design role. You will own how our projects get built: delivery method and contracting strategy, GC selection and oversight, MEP and specialty-systems coordination, cost and schedule control, and commissioning. Executing the design direction is set by the Global Head of Real Estate & Workplace and our architects. You will also lead and develop a team of project managers delivering across the global portfolio. This role reports to the Global Head of Real Estate & Workplace. Key responsibilities Pre-construction & technical delivery - Lead pre-construction on complex buildouts: constructibility and design/drawing reviews, MEP and structural coordination, estimating support, value engineering, and development of the GMP or bid package. - Recommend and own the delivery method and contracting strategy for each project (e.g., GMP, lump sum, CM-at-risk, design-assist), matching the approach to scope, schedule, and risk. - Read and interpret architectural, structural, and MEP drawings and specifications; surface gaps, conflicts, and risk before they reach the field. - Coordinate technically demanding scopes — commercial kitchens (Type I hoods, make-up air, grease and UL300 fire-suppression systems, utility upsizing), high-performance AV and acoustics for executive and event spaces, server/IDF rooms with redundant power and supplemental cooling, elevated power density, and integrated physical security. - Manage permitting and inspections with authorities having jurisdiction across multiple markets and labor environments. Construction execution, quality & closeout - Oversee construction from mobilization through closeout across multiple concurrent projects, holding general contractors accountable to schedule, budget, safety, and quality. - Run the technical processes that keep a job on track: RFIs, submittals and shop drawings, ASIs, and BIM/clash coordination across trades; lead owner-architect-contractor and trade-coordination meetings. - Conduct site visits to monitor progress, safety, and quality control; enforce inspection protocols and punch-list management. - Drive commissioning and closeout — systems commissioning (including kitchen exhaust/MUA balancing, BM

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is hiring a Field Marketing Manager dedicated to the Public Sector Industry — one of the fastest-growing customer segments we serve, and one we believe will define how the next generation of AI-native companies adopts and builds with Claude. You will own the field marketing strategy and end-to-end execution for Public Sector audiences in the US, partnering closely with our Public Sector Sales teams. This is a builder role. Field Marketing at Anthropic is a small, scrappy team and the Public Sector is an area of growth for the business — there is no existing playbook for you to inherit. You will design the event calendar, build the integrated digital programs, develop the necessary partnerships, and create the playbooks that scale across our Public Sector motion. Key responsibilities - Develop and activate the US Public Sector field marketing strategy end-to-end — planning, calendar, execution, and measurement. - Design and run public-sector-appropriate event formats — agency roundtables, mission-focused briefings, tech demo days, industry days, and executive breakfasts — that comply with government ethics and gift rules while building trusted relationships with program and procurement stakeholders - Plan the field calendar around the government fiscal year — building demand programs that peak ahead of federal year-end (September 30) and state budget cycles, and capitalize on use-it-or-lose-it spending windows - Own presence at anchor public sector events — from sponsorship strategy to speaker placement and on-site execution - Build co-marketing programs with the public sector channel ecosystem — distributors, resellers, systems integrators, and contract-vehicle holders — including joint events, teaming-oriented content, and partner-sourced pipeline - Partner closely with Public Sector Sales and BDRs on pre-event targeting, during-event engagement, and post-event follow-up to convert attention into pipeline - Build operational playbooks (Demo Day activation kit, hackathon kit) that the Field Marketing team can scale across regions and segments - Establish baseline metrics, dashboards, and ROI reporting for all Public Sector field programs - Be the face of Anthropic in the Public Sector ecosystem — credible with strategic partners and agencies You may be a good fit if you: - Direct Public Sector-segment experience — you have built and run programs targeting the Public Sector as your primary audience, not as an enterprise field marketer who occasionally touches Public Sector - End-to-end ownership of field marketing events and programs, hands on in both strategy and execution - this is a 0-1 building role with very little foundation in place - Repeat success across multiple companies — we are looking for a pattern of impact, scaling field or demand generation programs in different environments, not a single-company tour (however strong the brand) - 0-to-1 builder DNA — you've built a field marketing motion from scratch (or rebuilt one), and you also have scaled-company tenure that grounds you opera

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role You will be the finance partner to Anthropic's Enterprise sales team responsible for our largest technology and AI-native customers. In this role, you will be a key partner to our go-to-market teams, providing financial expertise and guidance to support strategic decision-making for a book of business scaling faster than almost any in software history, and you'll sit in the room where segment strategy gets decided. GTM Finance & Strategy sits at the epicenter of Anthropic's go-to-market decisions and you will play a crucial role in analyzing financial data, building models, and delivering insights to drive informed business decisions across revenue goals, sales capacity planning, deal desk and marketing spend returns. You'll be the person segment leaders turn to when they need to know where to invest, how to set targets, and whether a deal makes sense. Key responsibilities - Provide expert guidance, recommendations, and influence to go-to-market stakeholders on financial strategies, investments, and resource allocation decisions, leveraging an in-depth understanding of the company's financials - Own revenue forecasting and target-setting for a consumption-based business: build the models that translate usage dynamics, deal commitments, and model launches into credible plans - Collaborate with other members of strategic finance, FP&A, and accounting counterparts, helping to align go-to-market with broader financial strategies and considerations - Design and pressure-test sales capacity plans and variable compensation structures as the sales team scales - Deliver clear, decision-ready analysis to executives: what happened, why, and what we should do about it - Build the reporting infrastructure (dashboards, scorecards, self-serve metrics) that lets the business run itself; we work hands-on with data and use Claude to do finance in ways that don't exist anywhere else Minimum qualifications - Experience across strategic finance, go-to-market finance, private equity, growth equity, venture capital, consulting, and investment banking - Experience with consumption/usage-based revenue models (cloud infrastructure, API, or usage-priced products) — forecasting, unit economics, and deal structuring - Built operating models that executives actually used to make headcount, target, or investment decisions - Comfort pulling and shaping your own data (SQL or equivalent) and genuine enthusiasm for using AI tools to multiply your output - Ability to bring structure to ambiguous, zero-to-one problems and drive them to a conclusion under tight timelines - Exceptional analytical skills with an ability to synthesize data into compelling insights and develop / maintain complex financial operating models - Comfort working cross-functionally and are adept at communicating complex financial information to non-finance audiences - Excitement about working in a fast paced, dynamic environment and adapt well to change - Possess a bias towards action, strong work ethic,

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Finance Systems team builds and owns the infrastructure that powers our quote-to-cash lifecycle—from pricing and billing through revenue recognition and financial close. As our revenue model grows in complexity, the team is moving beyond configuring off-the-shelf platforms and into building homegrown, production-grade financial applications that no vendor has built for us yet. We are seeking a Finance Systems Engineer to join our Finance Systems team in San Francisco. In this hands-on engineering role, you will both configure and extend the third-party platforms that run our financial operations including Zuora, Stripe, and Tesorio and design, build, and own full-stack applications and integrations that sit on top of them. You will write production Python, Node.js, and React code, author Workato recipes and API integrations across our SaaS stack, administer and tune the systems themselves, and ship working software—not manage vendors or write requirements documents. You will work at the intersection of software engineering and finance, building and configuring the tools that allow our Accounting, Revenue Operations, and Order Management teams to operate efficiently, accurately, and in compliance with SOX and ASC 606 requirements. The first thing you will inherit is our homegrown ledger application and the integrations that connect it to Workday, NetSuite, Zuora, Stripe, Tesorio, and Salesforce. From there, you will help us build the next generation of Finance tooling: self-serve workflows, automated reconciliation, and the operational surfaces that let Finance move at the speed the business demands. If you thrive in fast-paced environments and enjoy building scalable financial infrastructure from the ground up, come join us in our mission to build safe, transformative AI. Responsibilities - Own the architecture, development, and maintenance of Anthropic's internal finance applications, and own the configuration and ongoing administration of third-party platforms such as Zuora, Workday, and Tesorio - Build and maintain integrations across the Finance systems stack: Zuora, Stripe, Workday, NetSuite, Salesforce, Tesorio, BigQuery and Billing applications - Design system integrations that are auditable, observable, and recoverable—with the rigor that SOX compliance demands - Identify manual, error-prone workflows in the month-end close and automate them with tested, production-grade solutions - Partner with Accounting, Revenue Operations, and Order Management teams to translate business requirements into scalable technical designs—and then build them yourself - Develop and maintain technical documentation, data flow diagrams, and runbooks so the team can operate systems without engineering dependency - Contribute to continuous delivery infrastructure so Finance systems can ship reliably and frequently - Instrument the Finance systems stack with observability tooling so the team knows when a pipeline breaks before the accountants do - Become the go-to domain expert f

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are seeking an experienced Technical Program Manager to support our critical cloud deployments. In this role you will be an execution owner, driving coordination and collaboration across multiple engineering teams. You will also support the collaboration and technical execution between our internal engineering teams and our major cloud partners including Amazon Bedrock, Google Vertex, and Microsoft Foundry. Your primary focus will be on ensuring tight coordination on engineering deliverables both within our internal teams and between our partner teams, enabling repeatable and efficient product development and launch pipelines for our AI models on third-party platforms. You will be responsible for aligning a range of business and technical stakeholders to drive execution of technical roadmaps, with a particular emphasis on optimizing our presence and performance. This position offers the opportunity to make a significant impact on Anthropic's growth and success in the cloud AI market, while working at the forefront of AI development and innovation. Responsibilities - Partner with engineering leaders to define, scope, and sequence major technical initiatives for cloud partnerships and AI model deployment, and own the plans, timelines, and resourcing to land them. - Own launch readiness for Claude models on partner cloud platforms: checklist, blocker tracking, joint go/no-go with the partner, and post-launch stability follow-through. - Act as the primary technical interface to cloud partner engineering orgs — owning the relationship, the shared roadmap, and day-to-day coordination on deployment, capacity, and incidents. - Drive cross-functional alignment across internal engineering, product, and go-to-market teams to land joint deliverables with the partner. - Provide clear and transparent reporting on program status, issues, and risks to executives and stakeholders. You may be a good fit if you - Have several years of experience in technical program management, with a track record of successfully delivering complex technical programs, preferably involving cloud platforms and AI technologies. - Have strong understanding of cloud computing architectures, AI/ML deployment, and integration challenges. - Have exceptional interpersonal and communication skills, enabling you to influence without authority and build cross-organizational support. - Have a high threshold for navigating ambiguity and ability to balance strategic priorities with rapid, high-quality execution. - Thrive in fast-paced, scaling environments with the ability to bring order to chaos. - Are passionate about Anthropic's mission and committed to ensuring AI is developed safely. Strong candidates may also have - Direct experience with a hyperscaler's managed AI platform — Amazon Bedrock, Google Vertex AI, or Azure AI Foundry — including how partners list, launch, and onboard customers on it. - Background in ML inference, model serving i

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Strategic Finance, GTM member to join our Finance team at Anthropic to partner with sales counterparts. In this role, you will be a key partner to our go-to-market teams, providing financial expertise and guidance to support strategic decision-making. As we continue to grow, you will play a crucial role in analyzing financial data, building models, and delivering insights to drive informed business decisions across revenue goals, sales capacity planning, deal desk and marketing spend returns. This role will work closely with cross-functional teams and collaborate with other members of the finance organization to align go-to-market strategies with broader financial considerations. Key responsibilities - Provide expert guidance, recommendations, and influence to go-to-market stakeholders on financial strategies, investments, and resource allocation decisions, leveraging an in-depth understanding of the company's financials - Partner cross-functionally to drive analysis, build financial models, and recommend business decisions across a variety of areas, such as revenue goals, sales capacity planning and key strategic initiatives - Prepare and deliver clear, concise, and insightful financial reports, analyses, and forecasts, highlighting key trends, risks, and opportunities to facilitate informed decision-making to stakeholders and executives - Collaborate with other members of strategic finance, FP&A, and accounting counterparts, helping to align go-to-market with broader financial strategies and considerations - Establish and implement reporting dashboards and scorecards to track key operational and financial metrics Minimum qualifications - Experience across strategic finance, go-to-market finance, private equity, growth equity, venture capital, consulting, and investment banking - Exceptional analytical skills with an ability to synthesize data into compelling insights and develop / maintain complex financial operating models - Extraordinary problem-solving and critical thinking abilities to navigate complex financial challenges - Comfort working cross-functionally and are adept at communicating complex financial information to non-finance audiences - Excitement about working in a fast paced, dynamic environment and adapt well to change - Possess a bias towards action, strong work ethic, and have experience driving operational outcomes under tight timelines - Strong relationship building, business judgment, process management, and communication skills - Are passionate ab

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are looking for a builder-minded Startup Partnerships lead to drive the adoption of Claude within India's dynamic and rapidly scaling startup ecosystem. This is a 0-to-1 opportunity — you'll be designing and executing innovative programs that enable startups to access and build with Claude across India's major tech hubs, from Bengaluru and Mumbai to Delhi-NCR, Hyderabad, and Pune. You will partner directly with leading Indian VCs, accelerators, and top startup customers to scale Anthropic's reach and impact. You'll define how Anthropic engages with one of the world's fastest-growing AI ecosystems and become a trusted AI advisor to founders and the VC community. India has emerged as a major global AI hub — home to a rapidly expanding cohort of AI-native startups, deep engineering talent, and world-class technical founders, and this role will put you at the centre of it. This role is for builders — someone founders see as a peer and trusted technical partner, not a traditional partnerships hire. You'll be hands-on with data, building your own dashboards, and shaping strategy through rigorous analysis. What You'll Do Drive Net New Logo Acquisition Through Developer Enablement - Develop and execute Anthropic's startup GTM strategy for India, identifying and prioritising top AI-native startups and building tiered engagement programmes that balance personalisation with scale. - Build strategic partnerships with leading Indian VCs that drive portfolio engagement. Design and launch strategic programmes with tier-1 VCs, own relationships end-to-end, negotiate partnership terms, and create exclusive benefits for portfolio companies. - Create compelling startup-focused offerings, pricing models, and growth initiatives in partnership with Indian accelerators and entrepreneurial communities - Build and maintain your own analytics infrastructure — design Hex dashboards, write SQL queries, and use data to drive programme optimisation and measure ROI. - Drive cross-functional coordination: Lead internal collaboration across Product, Engineering, Finance, Sales, and Corporate Development to ensure alignment on activation and penetration of accounts across the Indian startup ecosystem. Ecosystem Events & Community Building - In partnership with marketing, design and execute targeted events including builder summits, founder salons, hackathons, and demo days across key Indian tech hubs (Bengaluru, Mumbai, Delhi-NCR, Hyderabad, Pune, Chennai). - Partner with Indian accelerators and incubators to identify and engage the next wave of AI builders. - Build local developer communities around Claude through meetups, technical workshops, and content creation tailored to India's diverse and technically sophisticated builder community. VC & Ecosystem Partner Management &

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Business Development Representative at Anthropic, you'll drive the adoption of safe, frontier AI by optimizing our lead management processes and identifying new market opportunities. In this pivotal role, you'll enable our sales team to focus on high-value, revenue-generating activities by leveraging your analytical skills, project management expertise, and strategic thinking. Your role is critical in streamlining our sales pipeline and uncovering untapped potential in the AI market. Responsibilities: - Maintain full ownership of pipeline generating activities in your sales territory - Collaborate with sales teams to understand their needs and optimize lead handoff processes - Manage and prioritize a high volume of inbound leads - Conduct initial qualifications for high-potential leads - Outbound against strategic prospects to generate high-intent opportunities with Startup and Enterprise teams - Support the development and execution of strategic outbound initiatives - Provide data-driven insights to inform sales strategies and resource allocation - Continuously refine processes to improve efficiency and effectiveness You may be a good fit if you have: - 2-3+ years of experience in a fast-growing startup, preferably in a similar role - Strong analytical skills with the ability to translate data into actionable insights - Experience with Salesforce, HubSpot, and SQL (preferred) - Excellent communication and interpersonal skills - Ability to work in a fast-paced, dynamic environment - Passion for AI/ML and understanding of API-first or consumption-based business models - Fluent in Korean and English Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.&l

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As the Executive Briefing Program Lead, you will design, run, and scale the program that brings senior leaders from Anthropic's most strategic customers together with our spokespeople, product, and research teams. You will own the program end to end including qualification and intake, speaker selection, day-of execution, and post-briefing follow-through. You will own the agenda for briefings: setting its design and objectives, and developing it jointly with Product Marketing. You will also serve as the point of contact to account teams on how to use a briefing to move their most important opportunities forward. This is a highly cross-functional role. You will work closely with GTM and the Office of the CCO on account selection and program strategy, with Product Marketing on content development, with Solutions on technical deep-dives and demos, and with Anthropic's executive bench on sponsorship and participation. The right candidate has built or scaled an executive briefing program at an enterprise technology company, operates well at high volume, and is credible with both field leadership and C-level customers. Key responsibilities - Define and own the Executive Briefing program: briefing formats, qualification criteria, the request-and-intake process from Sales, capacity planning, calendar, and operating SLAs. - Govern which strategic accounts and executives receive a briefing each quarter in partnership with GTM leadership; hold the qualification bar and proactively surface accounts that should be engaged. - Lead discovery with account teams ahead of each briefing to understand the customer's objectives, business context, and where they are in their evaluation, and translate that into a tailored agenda. - Own agenda design and co-own agenda development with Product Marketing for every briefing. Shape the narrative arc and discussion topics to the customer's objectives, select discussion leaders and demos, and partner with PMM to build the briefing-specific content. - Build and manage the speaker bench: maintain the roster, match speakers to briefings, run prep, and manage capacity so no one is over-asked. - Own day-of orchestration and the customer experience standard for briefings, in partnership with our Workplace team on logistics. - Drive post-briefing follow-through: capture commitments and feedback, route them to owners, and track to close with the account team. - Build the playbooks, tooling, and best practices that let the program scale consistently as volume grows. - Own measurement and reporting, including briefing volume, strategic-account coverage, and program-influenced pipeline and expansion. Minimum qualifications - Built or significantly scaled an executive briefing program — you have defined qualification criteria, stood up an intake process, and managed a speaker bench. - Fluency with enterprise technology narratives — you're as comfort

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Join Anthropic's Customer Success team in a high-visibility & high-impact role driving AI adoption across our strategic Digital Native Business (DNB) accounts. As our dedicated Enterprise Customer Success Manager you'll work with our largest enterprise customers and be their strategic partner and trusted advisor helping them harness the full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code. You'll work with a global technology leader to actively deploy AI to reshape the technology landscape.You’ll be working with key partners who are moving fast and pushing the boundaries of what's possible with LLM technology. Your role will entail developing genuine partnerships with the customer and key stakeholders, gaining a deep understanding of their multi-pronged business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us. In partnership with the broader account team, you will help customers identify the right Claude capabilities for their specific business objectives, working closely with them to provide best practices and guidance while supporting them as their usage (consumption & seat based) grows and evolves. Your role focuses on helping customers scale their usage effectively, drive model and use case optimizations, implement change management strategies, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies — making you a key voice in shaping how we build and deliver ongoing value as a business. Responsibilities: - Build trusting, strategic relationships with key customer decision makers in complex, matrixed organizations; understand their business and objectives and identify opportunities for optimization and expansion - Become an expert in Anthropic's products across API, Claude Code and Claude for Enterprise, understanding the technical nuances and best practices for each to guide customers to the right solutions - Leverage your deep knowledge of the customer and other Digital Native Businesses to proactively drive usage planning, understanding current and future consumption/ adoption and how it creates realized value for the customer - Monitor usage patterns and identify optimization opportunities, proactively addressing underutilization across both consumption-based (API) and seat-based (Claude for Enterprise / Claude Code) products to drive full value from contracted commitments - Serve as the customer’s thought partner, enhancing their knowledge of Claude products by socializing Anthropic’s product roadmap, driving awareness on new products and engaging Product PMs - Document and quantify customer value realized through business outcomes, ROI, and impact metrics to build compelling internal business cases for continued and expanded investment - Identify potential use cases and lines of business not currently onboarded, partnering with customers and Sales/Product to discover new a

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we believe the next generation of Customer Success looks fundamentally different; most customer outcomes will be delivered through programs, not 1:1 relationships, and increasingly without a human in the loop. As a Success Programs Manager , you'll own a portfolio of those programs and flex across whatever the function needs to drive adoption and value at scale. As a CS Programs Lead you’ll think "How could we do this with Claude?" as a reflex — your default is to build an agent or an automated journey before you build a manual workflow. But you're also fluent in the craft of running engagements: you've personally designed and delivered 1:many webinars, stood up onboarding cohorts, and built communities that compound. You move comfortably between shipping an AI-native lifecycle flow on Monday and facilitating a live customer cohort on Tuesday. You'll work across the full Claude product surface, designing and shipping the programs that take customers from activation to value realization, expansion, and renewal. Instead of managing a book of accounts, you'll manage a portfolio of programs, each one a compounding asset that serves more customers, more effectively, every week it ships. You hold a high bar for measurable impact, you instrument what you build, and you retire what doesn't earn its keep. If the idea of a CS team that builds and ships as much as it joins calls excites you, and you want the range to do both, this role is for you. Key responsibilities: - Build and run a portfolio of programmatic CS plays (activation, scale and expand) across the long tail and unmanaged segments, spanning Claude Enterprise; Cowork, and Claude Code. - Design and ship Claude-powered engagement plays that replace or augment traditional CSM touchpoints: use-case discovery chats, digital QBRs, health reviews, feature nudges, consumption-drop saves, and expansion prompts. Define entry criteria, agent behavior, exit criteria, and success metrics for each. - Design and deliver high-leverage live engagements. 1:many webinar series, onboarding cohorts, customer communities, and academies, and look for every opportunity to make them AI-native, repeatable, and self-serve over time. - Flex across the needs of the function. Some weeks the priority is an agent; some weeks it's a cohort or a community launch. You bring comprehensive knowledge of what effective CS programs look like and apply the right model to the problem in front of you. - Instrument every program with consumption, product telemetry, and qualitative signals. Know which touchpoints — digital or live — deliver the most value and where the handoff between digital and human should sit, and invest accordingly. - Treat every cohort as an experiment. Continuously iterate on agent prompts, workflow logic, content, facilitation, and channel mix. Hold a high bar for measurable impact; kill plays that don't move the numbers. -

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enforcement Analyst focused on Bio Harms, you will play a critical role in protecting against the misuse of AI systems for biological and related CBRNE harms. You will enforce our Usage Policy with a specific focus on detecting and mitigating bio risks, investigating potential violations, and help continuously strengthen our safeguards. The work sits at the intersection of biosecurity threat analysis and platform enforcement: you will read real model interactions and make fast, well-reasoned calls about whether activity is benign research or a credible attempt at harm. This role is a fit for someone who understands the dual-use nature of biology and enabling technologies well enough to separate the benign from the malicious. You will own and continuously improve the enforcement monitoring workflows for the bio-harms area, and you will work closely with Policy, Threat Intelligence, Data Science, and Engineering cross-functional partners to accomplish tasks at scale. Safety is core to our mission, and your work will directly protect individuals, communities, and critical systems. Important context for the role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including material of a sexual, violent, or psychologically disturbing nature. The role also carries a shared on-call responsibility across the Policy and Enforcement teams. Key responsibilities - Enforce Usage Policies with a specific focus on detecting and mitigating potential bio risks and harmful use of AI systems. - Take ownership of enforcement monitoring workflows for the bio-harms area, improving end-to-end detection, investigation, triage, and escalation processes. - Monitor and analyze platform activity to identify emerging patterns related to biological (and adjacent chemical, radiological, nuclear, and explosive) threats that may require policy updates or enforcement action. - Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy across a technically complex content surface. - Conduct thorough investigations of potential violations, gathering and documenting evidence to support enforcement decisions. - Proactively surface trends and propose improvements to detection methods and review workflows. - Partner with Engineering and Data Science teams to optimize detection models and automated enforcement systems for bio-related policy violations. - Partner with Policy and Threat Intelligence groups to understand potential exploits and contribute to risk-assessment frameworks, and partner with engineers iterating on safety systems. - Provide enforcement-grounded feedback on policy gaps, and handle escalations and time-sensitive situations related to potential bio-related Usage Policy violations. Minimum qualifications - Hold a degree in a bio-related field (e.g., microbiology, molecular biology, biochemistry, public health) and/or relevant professional experience in a related field. - Possess experience in Trust & Safety, content moderation, or policy enforcement at platfo

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for an Engineering Manager to lead our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms. This is a foundational role: you'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes analytics capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly. As model capabilities and usage grow, you'll also drive how we scale review through automation — building systems where Claude meaningfully extends what human reviewers can do, while keeping people in the loop where their judgment matters most. You'll partner closely with policy, operations, data science, and legal teams to ensure our enforcement systems are effective, accurate, and trustworthy. Key responsibilities - Lead, grow, and develop a team of engineers building investigation, review, and enforcement tooling for both first-party and third-party platform surfaces - Define the vision and roadmap for our review tooling platform, including analytics, privacy-compatible data access primitives, and a sandbox for rapidly developing new review interfaces - Drive the team's strategy for scaling review through automation, including enabling reviewers to use Claude effectively and building toward Claude-assisted and Claude-driven review workflows - Partner with policy, operations, legal, privacy, and data science stakeholders to translate enforcement and investigation needs into reliable, well-designed systems - Ensure review tooling evolves alongside new privacy primitives and data retention commitments, so reviewers can do their work without compromising user trust - Create clarity for the team and stakeholders in an ambiguous and evolving environment - Take an inclusive, equitable approach to hiring and coaching top technical talent, and maintain a high-performing team - Contribute to engineering-wide initiatives as a member of Anthropic's engineering management community Minimum qualifications - Experience managing software engineering teams, including hiring, coaching, and developing engineers - A technical background in full-stack or platform engineering, with the ability to engage deeply in architecture and design discussions - Experience shipping internal tools or platforms with demanding operational users, and a track record of improving their workflows measurably - Experience working cross-functionally with non-engineering partners such as operations, policy, or legal teams - Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders - Care about the societal impacts of AI and want your work

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We're seeking an experienced Policy Communications Manager to help drive external communications for our security, governance, and responsible scaling programs, and associated work. This role offers the opportunity to help shape how Anthropic communicates about our approach to developing secure AI systems and products, our work to uphold and iterate on our Responsible Scaling Policy framework, and the unique corporate structure that keeps the company accountable to its mission, including our Long-Term Benefit Trust (LTBT) and our status as a public benefit corporation. You'll partner closely with our security, product, legal, governance, and Responsible Scaling Policy (RSP) teams to communicate Anthropic's approach to building safe and secure AI models as the technology becomes increasingly capable across critical domains like cybersecurity. You'll also help lead communications about how Anthropic is governed: the role of the LTBT's independent trustees in overseeing the company and electing members of our board, the obligations that come with our public benefit corporation charter, and why we believe this structure matters as AI systems grow more powerful. As governments establish regulatory frameworks for frontier AI, you'll help articulate how Anthropic approaches its transparency obligations and public reporting commitments, translating evolving requirements into clear, credible external communications. This will include balancing proactive storytelling about product security updates and launches with thoughtful handling of reactive matters as they arise. We're charting new terrain communicating about fast-moving frontier model capabilities and threat surfaces, and about institutional structures few other companies have built. You'll bring strong communications fundamentals to the role but recognize that traditional approaches may not map cleanly to the novel issues we're tackling. The ideal candidate is an experienced issues handler with strong executive management skills, attention to detail, and the judgment to navigate sensitive topics with care. You should be able to move quickly under pressure and tight deadlines, write crisply, and distill complex security, governance, and technical topics for a broad audience while maintaining accuracy. This is a unique opportunity to help define how one of the world's leading AI safety companies communicates about the security and governance challenges that will shape the future of the technology. Key responsibilities: - Develop and execute communications strategies for Anthropic's approach to AI security, governance, and responsible scaling - Drive external communications about Anthropic's corporate governance, including the Long-Term Benefit Trust and our public benefit corporation status, explaining how these structures provide independent oversight and accountability to our mission - Serve as a trusted communications partner to security, product, legal, governance, and RSP leaders on sensitive, fast-moving matters - Develop proactive communications around emerging regulatory frameworks and transparency obligations, including public reporting commitments, disclosure requirements, and Anthropic's engagement with oversight bodies - Manage reactive inbound media requests on complex security and governance topics -

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role You'll partner with Developer Productivity engineering leadership to define what "developer productivity" means in an AI-first org and to set the strategy for how Anthropic measures, understands, and improves it. This is a space where the playbook doesn't exist yet: AI-assisted development is reshaping how engineers work faster than anyone can measure, and last quarter's answer is already suspect. You'll decide which questions are worth asking, build the evidence to answer them, and stay ready to revise when the ground shifts again. You'll own the data strategy end-to-end: which metrics earn the org's trust, which investments to push for, which assumptions to challenge — including your own. The space rewards people who hold conclusions loosely, instrument early, and update fast when the data disagrees with the narrative. This role sits at the intersection of data science, developer experience, and frontier AI, with Anthropic's own teams as your users. Key responsibilities - Lead ambiguous, high-stakes investigations where the question isn't yet well-formed — from "is Claude making engineers faster?" to "what does 'faster' even mean here?" - Treat findings as provisional in a space that changes month to month. Bias toward instrumenting first, collecting evidence broadly, and revising the team's priors as the picture sharpens - Partner with Developer Productivity engineering leadership to set the team's measurement and research agenda — what to study, what to build, what to stop - Define the metrics framework for developer productivity in an AI-augmented org, and drive its adoption as the basis for tooling and infrastructure investment decisions - Design and run experiments on internal tooling and workflow changes; build the causal evidence base for what actually moves productivity - Influence engineering, infrastructure, and product leadership with data. Push back when the data doesn't support the prevailing narrative, and say so plainly when it doesn't support yours either <li class="font-claude-response-body whitespace-normal break-words pl-2" data-source

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As an Account Executive on Anthropic's Beneficial Deployments team covering nonprofits & higher ed institutions across APAC, you'll drive adoption of safe, frontier AI by securing strategic partnerships with nonprofit organisations, foundations, and higher education institutions across Asia-Pacific — with an initial focus on India, Australia/New Zealand, and Singapore. You'll leverage your consultative sales expertise to propel revenue growth while becoming a trusted partner to nonprofit, foundation, and university leaders, helping them embed and deploy AI to amplify their impact across programme delivery, teaching and research, fundraising, and operations. This role requires a strong understanding of both the social sector and higher education landscapes across APAC. In India this includes large NGOs, Section 8 companies, corporate CSR foundations, and philanthropic trusts; in ANZ, universities, peak bodies, and registered charities; in Singapore, universities, government-linked research institutes, and IPCs. You'll navigate region-specific regulatory frameworks — including India's DPDP Act and FCRA, the Australian Privacy Act, and Singapore's PDPA — and operate across diverse linguistic, cultural, and procurement contexts. The ideal candidate will be an exceptional salesperson with deep experience selling into the Indian market and exposure to APAC more broadly, a passion for developing new market segments, and the ability to operate autonomously as one of Anthropic's first commercial hires in the region while partnering closely with SF- and NY-based teams. By driving deployment of Anthropic's products across the APAC social and education sectors, you will help organisations amplify their impact on hundreds of millions of beneficiaries and learners while advancing the ethical development of AI. Responsibilities - Win new business and drive revenue for Anthropic across APAC nonprofits and higher education institutions — including large NGOs, corporate and philanthropic foundations, social enterprises, universities, and research institutes. Own the full sales cycle from first outbound to launch, managing complex procurement processes involving boards, trustees, CSR committees, provosts, CIOs, and university procurement - Design and execute innovative sales strategies tailored to the distinct market dynamics, regulatory environments, and procurement models of India, ANZ, and Singapore. Translate high-level regional plans into targeted sales activities and prioritise across a broad territory - Navigate complex stakeholder ecosystems — founders, trustees, CEOs, programme directors, and CSR heads on the nonprofit side; provosts, deans, CIOs, research leaders, and central IT/procurement on the higher education side — building consensus across founder-led, trust-governed, corporate-affiliated, and academic governance structures - Serve as Anthropic's regional expert on APAC nonprofit and higher education market dynamics, regulatory requirements, and competitive landscape. Provide insights that strengthen our value proposition and inform product roadmaps for APAC deployments, including localisation, language, and data residency priorities&lt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Enterprise is central to Anthropic's mission. The organizations that could benefit most from Claude are often the most demanding buyers, with rigorous requirements around security, compliance, and control. We believe earning their trust is essential to ensuring AI benefits the world broadly. We're looking for an engineering manager for our Enterprise pillar —the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, we're the team that makes it possible. You'll build the foundational systems that large organizations require before they can deploy AI at scale. This work directly converts product-market fit into revenue by removing the deployment blockers that prevent large organizations from adopting Claude broadly. This role sits at the intersection of enterprise product, platform infrastructure, and go-to-market. You'll partner closely with product, design, sales, and customer success to understand what our largest customers need, then translate those requirements into scalable technical solutions that work across Claude.ai , Claude Code, and API. Responsibilities - Lead and develop a team of engineers building out features and foundations that make Claude enterprise-ready at scale - Own engineering execution end-to-end: planning, prioritization, delivery quality, team health, and incident response - Partner with engineering teams throughout the company to ensure that the platforms we build are extensible and easy to adopt - Partner with sales and customer success on enterprise deals—understanding requirements, representing engineering in key conversations, and turning what you learn into priorities - Shape the roadmap with product and design, not just execute against it - Drive the compliance and platform-readiness work your customers require, partnering with security and legal - Recruit, onboard, and grow strong engineers; give direct feedback and build a healthy, high-performing team Minimum qualifications - 4+ years of experience as an engineering manager, with experience in enterprise SaaS, cloud services, or admin tools - Are comfortable executing at a fast pace to meet the expectations of our customers - Are detail-oriented and quality-focused - our customers are using Claude for critical workflows and our product needs to stay robust and reliable - Are comfortable working with enterprise customers, working alongside sales and customer success and joining customer conversations - Are a skilled engineering manager who treats management as a craft—clear feedback, strong 1:1s, consistent investment in your team's growth <

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Channel Account Manager for Japan, you will be responsible for building, managing, and scaling strategic partnerships with both System Integrators (SIs) and resellers to accelerate the adoption of our solutions in the Japanese enterprise market. You will work at the intersection of cutting-edge technology and Japan's unique business ecosystem, helping partners integrate our products into their solution portfolios and joint go-to-market strategies. As a Channel Account Manager, you will focus on growing reseller business in Japan and achieving quarterly revenue targets through new customers and upsells. The position involves direct collaboration with partners and internal teams to overcome obstacles and implement growth strategies. Responsibilities include designing partner recruitment, enablement, and go-to-market plans, using a test-and-learn approach in ambiguous situations. Strong business creation skills are needed to identify joint value propositions and explore co-selling models. While revenue contribution is the key metric, building scalable partner engagement and executing joint initiatives are crucial for consistent growth. This role is critical to establishing and expanding our presence in Japan through the partner ecosystem, enabling us to serve Japanese enterprises at scale. You will be instrumental in building our channel strategy from the ground up in one of the world's most sophisticated technology markets. Responsibilities: Strategic Partner Management - Develop and execute comprehensive business plans with System Integrators (NTT Data, Fujitsu, NEC, Hitachi, etc.) and key resellers to drive mutual growth and revenue targets - Build and maintain executive-level relationships within Japanese partner organizations, navigating complex organizational structures and decision-making processes - Own the full partner lifecycle from initial engagement through long-term strategic alignment, including regular business reviews and QBRs - Plan and deliver partner-facing activities, such as training sessions, email campaigns, webinars, and joint events - Negotiate and structure partnership agreements including technical integration terms, resale agreements, and revenue-sharing models Business Development & Revenue Generation - Build and maintain relationships with reseller and distributor partners to drive new customer acquisition and upsell revenue - Collaborate with SI partners and resellers to identify, qualify, and close enterprise opportunities in key verticals (manufacturing, financial services, retail, telecommunications, life sciences) - Drive joint sales activities including customer workshops, seminars, proof-of-concepts, and strategic account planning - Track pipeline development, forecast revenue, and report on partnership performance metrics with detailed accuracy - Manage channel conflic

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enforcement Analyst focused on Chem & Explosives Harms, you will play a critical role in protecting against the misuse of AI systems for chemical and explosives harms. You will enforce our Usage Policy with a specific focus on detecting and mitigating these risks, investigating potential violations, and help continuously strengthen our safeguards. The work sits at the intersection of chemical and explosives threat analysis and platform enforcement: you will read real model interactions and make fast, well-reasoned calls about whether activity is benign research or a credible attempt at harm. This role is a fit for someone who understands the dual-use nature of chemistry and explosives technologies well enough to separate the benign from the malicious — and who acts decisively under ambiguity. You will own and continuously improve the enforcement monitoring workflows for this harm area, and you will work closely with Policy, Threat Intelligence, Data Science, and Engineering matrix partners to accomplish tasks at scale. Safety is core to our mission, and your work will directly protect individuals, communities, and critical systems from AI-facilitated weapons harm. Important context for the role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including material of a sexual, violent, or psychologically disturbing nature. The role also carries a shared on-call responsibility across the Policy and Enforcement teams. Key responsibilities - Enforce Usage Policies with a specific focus on detecting and mitigating potential chemical and explosives risks and harmful use of AI systems. - Take ownership of enforcement monitoring workflows for the chemical and explosives harm area, improving end-to-end detection, investigation, triage, and escalation processes. - Monitor and analyze platform activity to identify emerging patterns related to chemical and explosives threats (within the broader CBRNE landscape) that may require policy updates or enforcement action. - Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy across a technically complex content surface. - Conduct thorough investigations of potential violations, gathering and documenting evidence to support enforcement decisions. - Proactively surface trends and propose improvements to detection methods and review workflows without waiting to be directed. - Partner with Engineering and Data Science teams to optimize detection models and automated enforcement systems for policy violations. - Partner with Policy and Threat Intelligence teams to understand potential exploits and contribute to risk-assessment frameworks, and partner with engineers iterating on safety systems. - Provide enforcement-grounded feedback on policy gaps, and handle escalations and time-sensitive situations related to chemical and explosives policy violations. Minimum qualifications - Hold a degree in a chemistry-related field (e.g., chemistry, chemical engineering, materials science) and/or relevant professional experience in a relate

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be recidivism: a ban that an actor can evade in five minutes isn't enforcement — it's friction. You'll own detecting when banned actors return, linking accounts across identities, and closing the re-registration paths that matter most. The mandate includes our highest-stakes populations, including preventing evasion of child-safety enforcement bans, where the cost of a missed return is unacceptable. This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Key responsibilities - Investigate evasion clusters end to end — from a single appeal or signal anomaly to the full linked actor network - Convert individual findings into durable systemic controls and detection proposals - Operationalize re-registration controls for high-severity ban populations - Partner with Engineering and Data Science teams on account-linking signals to connect returning actors across identities - Build the recidivism measurement framework: how often banned actors return, how fast we catch them, and which controls reduce return rates - Author playbooks for contractor-supported evasion review with QA against your own gold standard - Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows Minimum qualifications - Experience investigating ban evasion, multi-accounting, or repeat fraud actors at a platform with adversarial users - Fluency in SQL and comfort building your own analyses across large account and event datasets - Experience working with fraud or identity-linking signals and a working understanding of their precision/recall tradeoffs - Rigor about evidence standards — comfort with the asymmetric cost of false positives in severe-harm enforcement - A track record of turning one-off investigations into repeatable detection logic and policy - Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders - Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams Preferred qualifications - Experience using payment or network risk signals in an enforcement context - Experience with child-safety or other high-severity integrity enforcement - Experience collaborating directly with detection engineering or data science teams on rule deployment - A deep interest in AI safety and responsible technology development - Experience writing effective prompts for generative AI systems in a content revie

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Frontier AI is on track to be among the most consequential and most adversarially-targeted technology in the world. The capability curve is steep, the adversaries who want these systems are extremely well-resourced, and the security bar this will eventually require is well beyond where the industry operates today. Incremental hardening alone is not going to close that gap, so we need breakthroughs and a group of people to go find them. Security Labs is that team. We run a portfolio of high-risk, high-expected-value security projects: the work that seems impractical until someone optimistic and stubborn enough actually tries it. Projects run on the order of weeks rather than quarters, and each one is either handed off to the Anthropic team that will own it in production or wound down with a writeup of what we learned. We expect a meaningful fraction of our bets not to land. This is an experimental team and we expect a meaningful fraction of our bets not to land; the team itself is on a prove-out, engineers in this role need to be comfortable taking risks. If a 30% project success rate with that much ambiguity sounds uncomfortable or spending your time looking into uncharted and chaotic territory isn’t frightening and exciting, this probably isn't the right fit. There are other places in Anthropic Security doing important work with more structure, less risk, and more productive paths to positive outcomes. The questions we're trying to answer include: - Can our core research workflows survive extreme isolation? - Can we replace trust with cryptographic guarantees? - Can the models themselves become our most effective security control? - What would it actually take to defend against a tier-1 state adversary, and how much of that can we build now? Who we're looking for. We're hiring generalists with rare depth. You're a strong software engineer as a baseline, and on top of that you've gone deep in at least one area most engineers don't get near: firmware or hardware security, applied cryptography, OS / kernel / hypervisor internals, formal methods, reverse engineering, or high-assurance and cross-domain systems. You've built things under your own direction, you're comfortable jumping layers when the problem demands it, and you'd rather take a swing at something that might not work than ship the safe incremental thing. You think the trajectory of AI matters a great deal, you're not comfortable with how the security side of it is going by default, and you'd rather be on the inside building the answer than watching from outside. Current Project Areas The portfolio changes as we learn. The kinds of bets currently in flight or queued: - Standing up a prototype high-assurance research cluster: running real Anthropic training and research workloads under extreme isolation and physical security controls, and finding out exactly where productivity breaks and what we'd need to invent to get it back - Provable inference: cryptographic verification (zero-knowledge proofs, attestation chains) that a given output came from a specific model running specific code, replacing "trust us" with math - Shaping hypervisor-level workload isolation across our fleet

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a TPU Kernel Engineer, you'll be responsible for identifying and addressing performance issues across many different ML systems, including research, training, and inference. A significant portion of this work will involve designing and optimizing kernels for the TPU. You will also provide feedback to researchers about how model changes impact performance. Strong candidates will have a track record of solving large-scale systems problems and low-level optimization. You may be a good fit if you: - Have significant experience optimizing ML systems for TPUs, GPUs, or other accelerators - Are results-oriented, with a bias towards flexibility and impact - Pick up slack, even if it goes outside your job description - Enjoy pair programming (we love to pair!) - Want to learn more about machine learning research - Care about the societal impacts of your work Strong candidates may also have experience with: - High performance, large-scale ML systems - Designing and implementing kernels for TPUs or other ML accelerators - Understanding accelerators at a deep level, e.g. a background in computer architecture - ML framework internals - Language modeling with transformers Representative projects: - Implement low-latency, high-throughput sampling for large language models - Adapt existing models for low-precision inference - Build quantitative models of system performance - Design and implement custom collective communication algorithms - Debug kernel performance at the assembly level The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Pioneering the next generation of AI requires breakthrough innovations in GPU performance and systems engineering. As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible for maximizing GPU utilization and performance at unprecedented scale, developing cutting-edge optimizations that directly enable new model capabilities and dramatically improve inference efficiency. Working at the intersection of hardware and software, you'll implement state-of-the-art techniques from custom kernel development to distributed system architectures. Your work will span the entire stack—from low-level tensor core optimizations to orchestrating thousands of GPUs in perfect synchronization. Strong candidates will have a track record of delivering transformative GPU performance improvements in production ML systems and will be excited to shape the future of AI infrastructure alongside world-class researchers and engineers. You might be a good fit if you: - Have deep experience with GPU programming and optimization at scale - Are impact-driven, passionate about delivering measurable performance breakthroughs - Can navigate complex systems from hardware interfaces to high-level ML frameworks - Enjoy collaborative problem-solving and pair programming - Want to work on state-of-the-art language models with real-world impact - Care about the societal impacts of your work - Thrive in ambiguous environments where you define the path forward Strong candidates may also have experience with: - GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization - ML Compilers & Frameworks: PyTorch/JAX internals, torch.compile, XLA, custom operators - Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight - Distributed Systems: NCCL, NVLink, collective communication, model parallelism - Low-Precision: INT8/FP8 quantization, mixed-precision techniques - Production Systems: Large-scale training infrastructure, fault tolerance, cluster orchestration Representative projects: - Co-design attention mechanisms and algorithms for next-generation hardware architectures - Develop custom kernels for emerging quantization formats and mixed-precision techniques - Design distributed communication strategies for multi-node GPU clusters - Optimize end-to-end training and inference pipelines for frontier language models - Build performance modeling frameworks to predict and optimize GPU utilization - Implement kernel fusion strategies to minimize memory bandwidth bottlenecks - Create resilient systems for planet-scale distributed training infrastructure - Profile and eliminate performance bottlenecks in production serving infrastructure - Partner with hardware vendors to influence future accelerator

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Channel Account Manager for Japan, you will be responsible for building, managing, and scaling strategic partnerships with both System Integrators (SIs) and resellers to accelerate the adoption of our solutions in the Japanese enterprise market. You will work at the intersection of cutting-edge technology and Japan's unique business ecosystem, helping partners integrate our products into their solution portfolios and joint go-to-market strategies. As a Channel Account Manager, you will focus on growing reseller business in Japan and achieving quarterly revenue targets through new customers and upsells. The position involves direct collaboration with partners and internal teams to overcome obstacles and implement growth strategies. Responsibilities include designing partner recruitment, enablement, and go-to-market plans, using a test-and-learn approach in ambiguous situations. Strong business creation skills are needed to identify joint value propositions and explore co-selling models. While revenue contribution is the key metric, building scalable partner engagement and executing joint initiatives are crucial for consistent growth. This role is critical to establishing and expanding our presence in Japan through the partner ecosystem, enabling us to serve Japanese enterprises at scale. You will be instrumental in building our channel strategy from the ground up in one of the world's most sophisticated technology markets. Responsibilities: Strategic Partner Management - Develop and execute comprehensive business plans with System Integrators (NTT Data, Fujitsu, NEC, Hitachi, etc.) and key resellers to drive mutual growth and revenue targets - Build and maintain executive-level relationships within Japanese partner organizations, navigating complex organizational structures and decision-making processes - Own the full partner lifecycle from initial engagement through long-term strategic alignment, including regular business reviews and QBRs - Plan and deliver partner-facing activities, such as training sessions, email campaigns, webinars, and joint events - Negotiate and structure partnership agreements including technical integration terms, resale agreements, and revenue-sharing models Business Development & Revenue Generation - Build and maintain relationships with reseller and distributor partners to drive new customer acquisition and upsell revenue - Collaborate with SI partners and resellers to identify, qualify, and close enterprise opportunities in key verticals (manufacturing, financial services, retail, telecommunications, life sciences) - Drive joint sales activities including customer workshops, seminars, proof-of-concepts, and strategic account planning - Track pipeline development, forecast revenue, and report on partnership performance metrics with detailed accuracy -

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for a threat intel manager to build and run our Influence Operations & Surveillance team within Threat Intelligence. This team detects, investigates, and disrupts the misuse of Anthropic's AI systems for influence operations, coordinated inauthentic behavior, and surveillance operations by authoritarian states and the commercial spyware ecosystem. This is a ground-floor leadership role. The mission area today produces some of our most consequential casework and external reporting almost entirely through manual investigation; you will stand up its purpose-built detection capabilities, set the strategy for how a frontier AI company finds and counters state-linked information manipulation and surveillance misuse, and you'll personally be involved with the most complex investigations. Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. Key responsibilities - Own strategy, priorities, and outcomes for the Influence Operations & Surveillance threat intel mission area - Hire, manage, and develop a small team of technical threat investigators with IO and surveillance expertise - Personally lead investigations into state-linked surveillance misuse including commercial spyware vendors and surveillance products whose end customers are authoritarian governments and AI-enabled influence campaigns - Stand up the mission area's first automated detection: abuse signals, behavioral clustering, and coordinated-network detection tailored to information manipulation and surveillance tooling - Conduct cross-platform analysis linking on-platform activity to broader campaigns across social media, messaging platforms, and the spyware supply chain - Attribute campaigns to specific actors, with particular focus on state-sponsored operations from geopolitically significant regions - Own external engagement: government partners, platform integrity teams, academic and civil-society researchers, and threat intelligence sharing communities - Drive public and partner-facing reporting on AI-enabled IO and surveillance, and inform safety-by-design strategies as multimodal and agentic capabilities reshape the landscape Minimum qualifications - Have deep subject matter expertise in influence operations, coordinated inauthentic behavior, or state surveillance / commercial spyware ecosystems - Have led investigative teams or threat intel teams. - Have demonstrated proficiency in SQL and Python for data analysis and threat detection - Have experience attributing campaigns to specific threat actors, including state-sponsored operations - Have strong OSINT tradecraft for investigating online information ecosystems - Have hands-on experience with large language models and how they can be weaponized for IO and surveillance - Can present analytic

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Training and serving frontier AI models requires compute infrastructure at a scale and density that pushes past what conventional data center designs were built to handle. Anthropic’s Data Center team is responsible for delivering that physical infrastructure — partnering with build partners, equipment manufacturers, and utilities to stand up facilities that can reliably power some of the largest accelerator clusters in the industry. As a Data Center Electrical Engineer based in Japan, you’ll lead the electrical design of our facilities across our rapidly expanding Asia Pacific (APAC) portfolio — owning the architecture from the utility service entrance through to the rack. You’ll develop and maintain the reference designs and specifications our build partners work against, review their engineering submittals, and run the analysis needed to make confident decisions on topology, redundancy, and equipment selection. You’ll ensure the electrical architecture keeps pace with rapidly increasing rack densities and the unique load characteristics of large-scale ML training. This is a global role with a regional focus. You’ll bring fluency in the data center design conventions, codes, and supply markets of Japan, Korea, and the broader APAC region including Australia, and act as Anthropic’s on-the-ground electrical subject-matter expert with local utilities, agencies having jurisdiction, vendors, and contractors. It is also a highly cross-functional role: you’ll work with our hardware and compute teams to translate accelerator requirements into electrical design criteria, and with supply chain to qualify regional equipment vendors and create optionality in a constrained market. Strong candidates will bring deep mission-critical electrical design experience and the judgment to make sound trade-offs when the standard playbook doesn’t apply. Responsibilities Electrical design & engineering - Lead the electrical design of critical data center equipment across the APAC portfolio, including utility interface and substation, site-wide medium-voltage (MV) infrastructure, generators, uninterruptible power supplies (UPS), switchgear, transformers, and earthing/grounding systems. - Develop and maintain Anthropic’s electrical basis of design, reference architectures, and technical specifications for critical power distribution — covering switchgear, UPS systems, PDUs, busway, and rack power delivery — producing designs that meet or exceed our quality requirements while staying within budgetary targets. - Perform and validate engineering studies including short-circuit, coordination, arc flash, load flow, and power quality analysis; use findings to steer design decisions and equipment selection. - Read, interpret, and validate data center floor plans and technical drawings, and design and plan DC hall layouts for newly allocated spaces — including rack positioning, structured cabling, power distribution, and coordination with the cooling design. Partner, vendor & utility coordination - <p

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking an M&A Immigration Specialist to lead the immigration strategy behind our corporate transactions. As Anthropic grows through acquisitions and acqui-hires, you'll be the subject-matter expert ensuring that global talent moves seamlessly through every deal — from initial due diligence through close and beyond. You'll serve as the immigration advisor to our Corporate Development, Legal, and People teams, translating complex immigration questions into clear, actionable guidance for non-specialists and designing the integration plans that bring acquired employees onto Anthropic with continuity, certainty, and care. This is a high-trust, high-autonomy role at the intersection of immigration law, corporate transactions, and the employee experience. Key responsibilities - Lead immigration due diligence on prospective acquisitions and acqui-hires: evaluate the visa and green card posture of target workforces, identify portability and successor-in-interest considerations (PERM, I-140, H-1B), and quantify the immigration risk, cost, and timeline implications that inform deal decisions - Serve as the immigration advisor to Corporate Development, Legal, and senior leadership throughout the deal lifecycle, partnering with external counsel on novel or complex transaction-related filings - Design and execute integration plans for transferring foreign nationals, ensuring continuity of status through close, and providing white-glove support so that acquired employees experience a smooth, well-communicated transition - Maintain compliance with domestic and international employer obligations across transaction structures, and own documentation and record-keeping for acquired entities and populations (E-Verify, myUSCIS, and related systems) - Build the playbooks, frameworks, and policies that make M&A immigration repeatable and scalable as Anthropic's transaction volume and international footprint grow Minimum qualifications <ul class="[li_&]:mb-0 [li_&]:mt-1 [li_&]:gap-1 [&:not(:last-child)_ul]:pb-1 [&:not(:last-child)_ol]:pb-1 l

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for a threat intel manager to build and run our Model Exploitation & Fraud team within Threat Intelligence. This team detects, investigates, and disrupts the large-scale exploitation of Anthropic's AI systems. Model distillation, unauthorized access, account farming and reseller abuse, and fraud and scam operations. You will set the strategy for the mission area, hire and lead a small team of technical investigators, and build the systems, processes, and partnerships that let the team scale. The team includes established senior investigators who own our deepest technical casework, tracing distillation networks, reseller and proxy ecosystems, and financially motivated actors across first-party surfaces and third-party platforms; your job is to direct, resource, and amplify that work, not duplicate it. This area carries regular U.S. government engagement and requires deeply understanding external black market ecosystems and how they interact with our systems. Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. Key responsibilities - Own strategy, priorities, and outcomes for the Model Exploitation & Fraud mission area; define what we detect, investigate, action, and share - Hire, manage, and develop a team of technical threat investigators; set the quality bar for casework and intelligence reporting - Design clear lanes between this role and the team's senior individual contributors: strategy, people leadership, and program ownership sit with you, while ownership of the deepest technical investigations and tradecraft stays with the senior experts closest to the work - Capable of independently leading complex investigations. - Direct, prioritize, and resource complex investigations into model distillation, unauthorized AI R&D usage, unauthorized access, coordinated account abuse, and fraud/scam networks, partnering with the senior investigators who lead the deepest technical casework and clearing blockers from their path - Drive the redesign of triage for a very high-volume detection pipeline: partner with investigators and engineering to build abuse signals, clustering, and agentic investigation workflows that separate sophisticated actors from noise - Expand the team's coverage into fraud and scams, building the detection and investigation playbooks from the ground up - Own the external engagement program for the area, including regular intelligence sharing with U.S. government partners and industry peers, ensuring the investigators driving the work are visible in those channels - Anticipate how resellers, proxies, and third-party platforms change the abuse surface, and shape coverage accordingly - Work with policy, enforcement, and engineering to convert findings into bans, product mitigations, and safety-by-design improvements - Define and report the team's metrics; brief Safeguards and company leadership on the threat landscape <

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As the Manager of the Partnerships Applied AI Solutions Architect team, you will drive adoption of frontier AI by enabling deployment of Anthropic’s products (Claude for Enterprise, Claude Code, API) through our Global and Regional System Integrators, cloud partners (AWS, GCP, Azure), and strategic technology partners. You will build and lead a team of Partner Solutions Architects, establish processes and best practices for partner-led pre-sales engagements, and represent Anthropic as the technical lead on its most important partnerships. In collaboration with Sales, Partnerships, Product, and Engineering, you will help partners incorporate leading-edge AI into their practices, accelerate indirect revenue, and execute long-term GTM strategy while maintaining our best-in-class safety standards. Responsibilities - Team Leadership & Development: Hire, manage, and mentor a team of Partner Solutions Architects. Set goals, run reviews, and coach each team member toward high productivity and career growth. - Strategic Technical Partnership: Act as the senior technical thought partner to Anthropic’s GTM partnerships team. Co-build partner strategy with aligned GTM leadership, drive key programs, and align cross-functional stakeholders (Sales, Product, Engineering) behind partner outcomes. - Partner Enablement & Ecosystem: Embed your team with GSI and cloud partner technical teams to enable their AI practices, troubleshoot, and evangelize Anthropic in their developer communities. Represent Anthropic at partner events (GSI workshops, AWS/GCP summits, hackathons) and contribute technical content and thought leadership. - Joint Solution Development: Lead partners in identifying high-value, industry-specific GenAI applications. Develop joint solutions and codify reference architectures and best practices to accelerate time to deployment. - Customer Deal Support: Own the technical portion of partner-led pre-sales engagements. Intervene directly on strategic deals where partners are the primary delivery vehicle, providing deep solution architecture guidance. - Product Feedback: Gather and validate feedback on Anthropic’s products from partner deployments and deliver it to Product and Engineering to inform roadmap and partner strategy. You may be a good fit if you have - 7+ years in technical customer-facing or partner-facing roles (Solutions Architect, Sales Engineer, Partner SE, TAM). - 3+ years managing pre-sales or partner-facing technical teams; comfortable building foundational teams in ambiguous, fast-moving environments. - Track record building and scaling partnerships with GSIs (e.g., Accenture, Deloitte, TCS, Infosys) and/or cloud providers (AWS, GCP, Azure). - Deep understanding of partner-led selling and delivery: indirect revenue models, enablement at scale, and joint GTM motions. - Technical depth in enterprise AI deployments: LLM architecture, prompt engineering, evaluation, API i

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your focus will be driving a number of enforcement areas including access controls and identity verification. You'll own the policy layer of these systems: what we ask users for, when, on what grounds, and what passes. The work sits at the intersection of policy, operations, and regulatory exposure. This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Key responsibilities - Set collection policy for identity signals: what we request, in which enforcement states, and what evidence reinstates access - Improve verification program health — accuracy, appeal coverage, and consistency of outcomes - Own access policy for hard cases, including geographic restrictions and reseller arrangements - Run the operational queue for access-control cases alongside contractor support, authoring playbooks and QA'ing scaled review output - Work with Legal, Public Policy, and Privacy stakeholders to keep our approach proportionate, privacy-preserving, and responsive to an evolving regulatory landscape - Coordinate enforcement consistency with third-party platform partners - Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows - Stand up graduated enforcement in practice — verification requests, conditional reinstatement, and appeal pathways that satisfy regulatory requirements for automated decisions Minimum qualifications - Experience in trust & safety, integrity, or risk policy work - Hands-on operational experience — you've owned or quality-checked live enforcement queues, not only authored policy - Subject matter expertise in one or more of: KYC, identity verification, age or identity assurance, or verification program operations - Experience navigating evolving regulatory landscapes (including frameworks like the DSA and GDPR) as design constraints rather than blockers - Experience driving cross-functional initiatives with Product, Engineering, Legal, and Policy partners — especially where safety, privacy, and usability tradeoffs need to be navigated together - Comfort using data (SQL or similar tools) to measure what's working and inform decisions - Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders - Excellent judgment and the ability to make consistent, defensible calls on ambiguous cases Preferred qualifications - Experience with graduated/tiered enforcement systems rather than binary ban models - Experience with geographic access restrictions, sanctions screening, or

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst focused on Violence & Extremism, you will be responsible for building and executing operational workflows to assess model behavior, drive enforcement decisions, and develop evals across a technically demanding range of policy areas. Your work spans detecting and mitigating attempts to misuse Anthropic's AI systems to facilitate real-world harm, including weapons and dangerous technology, critical infrastructure attacks, violent extremism, and threats of violence. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a violent, graphic, hateful, or psychologically disturbing nature. Key responsibilities - Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy - Develop and maintain evals that measure model performance on these policy areas, surface regressions, and inform policy and model improvements - Partner with Engineering and Data Science to optimize detection and automated enforcement systems for potential policy violations - Review flagged content to drive enforcement decisions and surface policy gaps, with particular attention to novel or technically sophisticated misuse attempts + emerging extremist movements, ideologies, and mobilization tactics - Support the Safeguards policy design team by providing structured feedback on policy gaps and enforcement ambiguities based on real enforcement scenarios - Develop and maintain enforcement guidelines and reviewer documentation that enable accurate, consistent enforcement across a wide range of content - Keep up to date with emerging threats, terrorist and extremist movements, regulatory changes, and AI policy enforcement best practices, and apply these to inform our workflows and evals - Identify and escalate emerging misuse patterns, novel attack vectors, and signs of coordinated violent extremist activity Minimum qualifications - Experience in policy enforcement, threat intelligence, counterterrorism, government, or a closely related field, with direct exposure to harmful content, dangerous technology, violent extremism, or physical harm facilitation - Experience standing up and scaling policy enforcement or content review workflows - Proficiency in SQL and/or other data analysis tools to draw insights from large datasets and monitor enforcement workflow health - Experience identifying emerging risks and threat actors, and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams - Experience working with generative AI products, including writing effective prompts for content review and enforcement - Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space Preferred qualifications - Subject ma

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As Data Operations Manager, you'll build and scale data operations across research teams working on frontier AI capabilities. You'll partner with researchers to design and execute data strategies, manage vendor relationships, and own the entire data pipeline from requirements to production. This role requires operational excellence combined with technical depth to understand what makes high-quality training data, but your focus will be on strategy and execution. About the Impact The data operations you build will directly determine how well our models perform on critical capabilities—tool use accuracy, prompt injection robustness, long-horizon reasoning, and safety alignment. You'll work with world-class researchers advancing the frontier while building the operational infrastructure to scale these efforts. We're looking for someone who gets excited about the challenge of scaling quality across diverse research areas—someone who can understand nuanced technical requirements, build the right partnerships, and execute flawlessly. If you thrive at the intersection of operational excellence and cutting-edge AI research, we'd love to hear from you. Responsibilities: - Own and execute data strategy for research teams advancing frontier AI capabilities across RLHF, safety, tool use, and agentic workflows - Drive strategic vendor partnerships and build scalable frameworks for technical data collection at scale - Design and implement operational systems that translate research requirements into high-quality data pipelines - Build evaluation frameworks and quality standards that ensure data meets the bar for training state-of-the-art AI systems - Lead cross-functional initiatives to optimize research velocity while maintaining rigorous quality standards - Proactively identify risks, bottlenecks, and opportunities to improve efficiency and effectiveness across data operations - Partner with senior research leaders to align data operations with model development roadmaps and strategic priorities You may be a good fit if you: - Have 3+ years in operations, consulting, product management, or program management roles - Have exceptional project management skills with ability to handle multiple complex projects simultaneously - Have strong communication skills and can engage effectively with technical and non-technical stakeholders - Are familiar with how LLMs work or have strong interest in understanding AI training methodologies - Are highly organized and can navigate ambiguity effectively - Have experience with data analysis tools (SQL, Python, Tableau, spreadsheets, or similar) - Thrive in fast-paced research environments with shifting priorities - Are passionate about AI safety an

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic’s Finance Analytics & Business Intelligence team is hiring a senior individual contributor to own how we measure the value of our models and our position in the market. These are open questions without an established playbook: how much value do our models deliver per dollar and per token, how is that changing with every launch, how do we compare to the rest of the frontier? You’ll own how Finance quantifies relative model value and market position: maturing our cross-product benchmark suite, building task-cost and price-elasticity estimates that inform live pricing and packaging decisions, sourcing and running capability and market analysis around every model launch, and standing up forecasting on third-party and survey data. The work is open-ended and technical, and you’ll operate as an analytical lead, partnering closely with Product Finance and our model performance Data Science teams. Key responsibilities - Build the relative-value measurement system: evolve our cross-product benchmark into a durable, trusted read on model and product value, spanning coding, agentic, and product-shaped tasks - Inform pricing and packaging: construct task-cost approximations and price-elasticity estimates across differently priced products, and carry them into decisions - Own launch and market analytics: run analytics around model launches, including capability-based revenue analyses and views of the broader market - Deepen our market understanding: evaluate and integrate external datasets and research to strengthen our read on the market and how it's evolving - Partner with Product Finance: take open-ended pricing, packaging, and positioning questions from vague ask to decision-grade answer - Raise the bar: land narratives in executive forums and uplevel the team’s product-finance analytics practice by example Minimum qualifications - Put shape around ambiguity: you’ve personally defined the measurement approach for questions nobody knew how to answer, without waiting for a fully specified ask - Land narratives with executives: your analyses have changed pricing, product, or competitive decisions, and you can simplify for senior leaders without losing rigor - Stay hands-on at senior scope: you still write the SQL and Python yourself, and you’d rather ship a defensible v1 with honest error bars than wait for perfect data - Are inherently curious: you go one level deeper than asked and are energized by how fast models, products, and the market are moving - Thrive amid shifting priorities: you juggle multiple fast-moving workstreams and stay effective when the plan changes weekly - Work fluently with modern tooling: you’re strong at data visualization,

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be standing up fraud & scams enforcement as a program: today this work is handled reactively and in fragments — payment fraud, promotional abuse, and scam-pattern enforcement don't yet have a single owner. You'll be that owner: defining the policy area, building the detection-to-enforcement pipeline, and setting the operating model that a contractor bench can execute against. The surface area is broad: payment fraud (stolen cards, chargebacks, disputes), promotional and credits abuse, and the use of accounts to run scams against third parties. This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Key responsibilities - Define the fraud & scams policy taxonomy and how cases are classified, prioritized, and escalated - Investigate and dismantle organized abuse rings, converting findings into durable controls - Stand up proactive fraud detection and customer-facing communication flows for fraudulent organization cases - Build the dispute and chargeback strategy in partnership with payments and card-network partners - Quantify fraud losses and control efficacy to drive investment decisions - Author the contractor playbook for fraud review and own QA of scaled output - Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows Minimum qualifications - Deep payment-fraud experience at a fintech, marketplace, or platform — chargebacks, disputes, card-testing, promotional abuse - Experience building or significantly scaling a fraud program from an early state, not just operating a mature one - A working command of payment-network and dispute mechanics, sufficient to make strategy calls on them - Comfort being the sole owner of an area: prioritizing ruthlessly, shipping iteratively, and asking for help precisely - Comfort using data (SQL or similar tools) to quantify fraud losses and control efficacy - Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders - Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams Preferred qualifications - Experience working directly with payment service providers and card networks on fraud strategy - Experience with scam typologies beyond payments — social engineering, impersonation, platform-mediated scams - Experience managing vendor relationships in the fraud/risk detection space - A deep interest in AI safety and responsible technology development <li&g

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enforcement Analyst focused on Radiological & Nuclear Harms, you will play a critical role in protecting against the misuse of AI systems for radiological and nuclear harms. You will enforce our Usage Policy with a specific focus on detecting and mitigating these risks, investigating potential violations, and help continuously strengthen our safeguards. The work sits at the intersection of radiological and nuclear threat analysis and platform enforcement: you will read real model interactions and make fast, well-reasoned calls about whether activity is benign research or a credible attempt at harm. This role is a fit for someone who understands the dual-use nature of radiological and nuclear knowledge and enabling technologies well enough to separate the benign from the malicious — and who acts decisively under ambiguity. You will own and continuously improve the enforcement monitoring workflows for this harm area, and you will work closely with Policy, Threat Intelligence, Data Science, and Engineering cross-functional partners to accomplish this. Safety is core to our mission, and your work will directly protect individuals, communities, and critical systems from AI-facilitated weapons harm. Important context for the role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including material of a sexual, violent, or psychologically disturbing nature. The role also carries a shared on-call responsibility across the Policy and Enforcement teams. Key responsibilities - Enforce Usage Policies with a specific focus on detecting and mitigating potential radiological and nuclear risks. - Take ownership of enforcement monitoring workflows for the radiological and nuclear harm area, improving end-to-end detection, investigation, triage, and escalation processes. - Monitor and analyze platform activity to identify emerging patterns related to radiological and nuclear threats (within the broader CBRNE landscape) that may require policy updates or interventions. - Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy across a technically complex content surface. - Conduct thorough investigations of potential violations, gathering and documenting evidence to support enforcement decisions. - Proactively surface trends and propose improvements to detection methods and review workflows. - Partner with Engineering and Data Science teams to optimize detection models and automated enforcement systems for policy violations. - Partner with Policy and Threat Intelligence teams to understand potential exploits and contribute to risk-assessment frameworks, and partner with engineers iterating on safety systems. - Provide enforcement-grounded feedback on policy gaps, and handle escalations and time-sensitive situations related to radiological and nuclear policy violations. Minimum qualifications - Hold an undergraduate degree in a physics- or nuclear-related field (e.g., physics, nuclear engineering, health physics, radiochemistry) and/or relevant professional experience in

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Join Anthropic's Customer Success team in a high-impact role driving AI adoption across our Industry segment. As an Enterprise Customer Success Manager for Industries, you'll be the strategic partner and a trusted advisor to our most complex customers with a portfolio spanning Financial Services, Systems Integrators, Semiconductor, Manufacturing and Retail organizations—helping them harness the full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code. You'll work with organizations across diverse industries that are transforming their businesses with AI technology. Developing genuine partnerships with customers, gaining a deep understanding of their business objectives, strategic direction, AI vision, and technical needs. You'll draw on both your business acumen and technical expertise to serve as a strategic advisor throughout their journey with us. In partnership with the broader account team you will help customers identify the right Claude capabilities for their specific business objectives, working closely with them to provide best practices and guidance while supporting them as their usage (consumption & seat based) grows and evolves. Your role focuses on helping customers scale their usage effectively, drive model and use case optimizations, implement change management strategies, and maximize the value of their investment through expanded use cases across their organization. The insights you gather from your customers will directly inform our research priorities, product development, and go-to-market strategies — making you a key voice in shaping how we build and deliver ongoing value as a business. Responsibilities: - Build trusting, strategic relationships with key customer decision makers to understand their business and objectives, identifying opportunities for optimization and expansion - Become an expert in Anthropic's products across API, Claude Code and Claude for Enterprise, understanding the technical nuances and best practices for each to guide customers to the right solutions - Leverage your deep knowledge of the customer and their industry vertical to proactively drive usage planning, understanding current and future consumption/adoption and how it creates realized value for the customer - Monitor usage patterns and identify optimization opportunities, proactively addressing underutilization across both consumption-based (API) and seat-based (Claude for Enterprise / Claude Code) products to drive full value from contracted commitments - Serve as the customer's thought partner, enhancing their knowledge of Claude products by socializing Anthropic's product roadmap, driving awareness on new products and engaging Product PMs - Document and quantify customer value realized through business outcomes, ROI, and impact metrics to build compelling internal business cases for continued and expanded investment - Identify potential use cases and lines of business not currently onboarded, partnering with customers and Sales to discover new applications for Claude across different departments, teams, and workflows - Develop and execute change management strategies to drive end-user adoption and maximize

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is the responsible development and maintenance of advanced AI for the long-term benefit of humanity. We are a safety-focused AI company working to build reliable, interpretable, and steerable AI systems. As our compute infrastructure scales to support frontier model training and deployment, we are building a world-class team to design, deliver, and operate the physical facilities that make that possible. About the Role We are looking for a Principal Data Center Architect with deep expertise in Civil, Structural, and Architectural (CSA) design to join our growing infrastructure team. This role is the technical owner for the physical building fabric of Anthropic's AI compute facilities — from the earliest site feasibility studies and test fits through reference design development, design partner oversight, and construction delivery. As Anthropic scales its data center program across multiple sites in the United States and internationally, you will set the civil, structural, and architectural standards that govern how our facilities are designed and built. You will work directly with design-build partners, AE firms, and internal mechanical, electrical, and IT infrastructure teams to ensure our facilities are optimized for high-density AI workloads, constructable on aggressive timelines, and replicable across a growing portfolio. This is an owner's engineer role — you are the technical authority, not a consultant. You will be expected to make binding design decisions, identify problems before they reach the field, and drive standardization across a pipeline of concurrent projects globally. What You'll Do - Own the civil, structural, and architectural reference design standards for Anthropic's data center portfolio, establishing repeatable design elements deployable across multiple sites and jurisdictions - Lead front-end test fits and site feasibility studies, evaluating structural approaches, site constraints, utility interfaces, and code compliance to inform site selection and design direction - Review and approve CSA deliverables from design-build partners and AE firms at each design stage (SD, DD, CD, IFC), including drawings, structural calculations, specifications, and geotechnical reports - Integrate CSA design with mechanical, electrical, plumbing, fire protection, and IT infrastructure teams to produce coordinated designs that support high-density AI compute and direct liquid-cooling systems - Drive site and campus planning to maximize compute density, optimize construction phasing, and align physical layout with IT and operational requirements - Partner with the construction and delivery team to provide technical oversight during construction, resolve field issues, and support commissioning activities - Evaluate and develop relationships with design partners, structural engineering subconsultants, and prefabrication / modular vendors; define qualification and performance standards <

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the user well-being team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be on how Anthropic handles age. A core part of this work is making sure our consumer products reach the right audiences, including the detection signals, verification paths, and appeals workflows that keep underage users off surfaces not designed for them. Claude also reaches younger users through third-party developers building on our API, and you'll be the enforcement partner that sales and platform teams rely on when those customers need guidance on deploying age-appropriately. This position may expand into broader areas of user well-being enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. There is also an on-call responsibility across the Policy and Enforcement teams. Key responsibilities - Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy - Partner with Engineering and Data Science teams to optimize detection models for policy violations and automated enforcement systems - Review flagged content to drive enforcement and policy improvements - Enforce usage policies with a focus on detecting and mitigating potential harmful use of AI systems - Work with Legal, Public Policy, and Privacy stakeholders to keep our age assurance approach proportionate, privacy-preserving, and responsive to an evolving regulatory landscape - Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios - Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows - Responsible for Anthropic's layered age assurance approach - self-declaration, behavioral signals, verification, and ban appeals - to keep our first-party consumer products safe - Adjacent user well-being enforcement where age is a key factor in how policy is applied such as sexual content and illicit substances Minimum qualifications - Experience in trust and safety, online child safety, age assurance, privacy, product policy, or a related field - Subject matter expertise in one or more of: age assurance or age verification systems, age-appropriate design, child online safety, privacy-preserving verification methods, or content classification for young people - Experience driving cross-functional initiatives with Product, Engineering, Legal, and Policy partners — especially where safety, privacy, and usability tradeoffs need to be navigated together - Experience navigating evolving regulator

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Apply using this link . Applications for the next cohort of Anthropic Fellows close at 11:59pm PT on July 26 . The cohort is expected to start November 2 . In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the November start date doesn't work for you. This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting . Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect - 4 months of full-time research - Direct mentorship from Anthropic researchers - Access to a shared workspace (in either Berkeley, California or London, UK) - Connection to the broader AI safety and security research community - Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) - Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research progra

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Join Anthropic as a Customer Success Manager supporting our Beneficial Deployments team’s initiatives in Global Development. In this role, you’ll apply enterprise-grade customer success practices to partnerships with mission-driven organizations. Anthropic’s Beneficial Deployments team is focused on building AI for good through partnerships with high-impact organizations. As their dedicated Customer Success Manager, you’ll be the strategic partner and trusted advisor to these organizations - helping them harness Claude’s full potential of all our Claude capabilities - API, Claude for Enterprise, and Claude Code to amplify their social impact. You’ll develop genuine partnerships with organizations, gaining a deep understanding of their mission, strategic objectives, programmatic goals, and technical capacity. Drawing on your global development expertise, business acumen, and technical knowledge, you’ll serve as a strategic advisor throughout their journey—helping them identify the right Claude capabilities for their specific objectives while providing best practices tailored to the unique needs of these institutions. Your role focuses on helping global development organizations scale their AI adoption effectively, implement change management strategies suited to mission-driven cultures, optimize use cases for maximum social impact, and demonstrate value that supports continued investment and expansion. The insights you gather from these partnerships will directly inform our research priorities, product development, and strategies for beneficial AI deployment—making you a key voice in shaping how we build and deliver AI systems that amplify social good. Key responsibilities: • Build trusting, strategic relationships with nonprofit leaders, program officers, and mission-driven stakeholders to understand their organizational goals, programmatic needs, and social impact objectives, identifying opportunities for optimization and expanded AI deployment in service of supporting their organizational transformation. • Become an expert in Anthropic’s products across API, Claude for Enterprise, and Claude Code, understanding the technical nuances and best practices for each to guide customers to the right solutions • Monitor usage patterns and proactively drive adoption—identifying optimization opportunities, addressing underutilization across consumption-based (API) and seat-based products, and discovering new applications for Claude across departments and workflows • Develop and execute change management strategies appropriate for mission-driven organizational cultures, driving adoption through Train the Trainer programs, Center of Excellence development, and organizational enablement that respects partner capacity constraints and decision-making processes • Create and maintain customer enablement resources—identifying opportunities to develop scalable assets that drive efficiency across the partner portfolio • Serve as the customer’s thought partner, enhancing their knowledge of Claude products by socializing Anthropic’s prod

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Startup Account Executive at Anthropic, you'll manage a portfolio of startup customers and help them harness the transformative potential of safe, frontier AI. This role is designed for early-career sales professionals who thrive in fast-paced environments and are excited about building scalable engagement models. You'll leverage Claude and other tools to efficiently serve a large customer base while identifying high-potential accounts for growth. The ideal candidate will combine strong foundational sales skills with intellectual curiosity about AI and a passion for process improvement. You'll develop playbooks for scaled customer engagement that benefit the entire Growth AE organization, while building the skills to advance into more senior AE roles. Responsibilities: • Manage a portfolio of 100+ startup accounts, maintaining high retention and identifying expansion opportunities • Build and execute scalable engagement models using Claude and automation to efficiently serve a high-volume customer base • Identify breakout accounts with high growth potential and ensure smooth transitions to expanded coverage when appropriate • Develop and document best practices for scaled customer engagement that can be shared across the Growth AE organization • Conduct streamlined account health checks and identify early warning signs of churn risk • Partner with customers to understand their business models and product, advising them through their AI transformation, and gathering feedback to inform product development • Collaborate with Applied AI and other cross-functional teams to support customer technical needs You may be a good fit if you have: • 3+ years of experience in sales, account management, customer success, or related roles • Demonstrated ability to manage multiple priorities and a high volume of customer relationships simultaneously • Strong communication skills with ability to build rapport quickly across various customer personas • Analytical mindset with comfort using data to prioritize accounts and identify trends • Enthusiasm for emerging technologies and genuine interest in AI • A "roll up your sleeves" mentality and comfort operating in ambiguous, fast-changing environments Strong candidates may have: • Experience with consumption-based or usage-based pricing models • Familiarity with technical products, APIs, or developer-focused solutions • Experience working with startup customers or in a high-growth startup environment • Exposure to AI/ML concepts and applications The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the s

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role This is a senior, foundational role on a new team: you'll make architecture decisions the rest of the team builds on, and help shape what we build first. The work is hands-on and varied. Some weeks you'll be deep in pipeline or infrastructure engineering; others you'll be tuning prompts until the output is good, or sitting with a research team that depends on your systems and shipping the fixes they need. We're looking for experienced engineers who own outcomes end-to-end — down to reading transcripts, supporting users, and wrangling vendors. Anthropic's RL Data team builds the systems that produce high-quality reinforcement learning data for Claude: data collection pipelines, human feedback tooling, the execution environments RL tasks run in, and the quality assurance that keeps training data trustworthy at scale. Our goal is to make Claude great at real work — especially the work that matters most, like AI safety research and beneficial deployments of AI. (To be upfront: this is dual-use work — it advances general capabilities too.) Key responsibilities - Own significant parts of our stack end-to-end, from technical architecture through the unglamorous operational work that makes it succeed. - Build data collection pipelines, read the transcripts they produce, and iterate on prompts, evals, and graders until the output is good. - Develop and improve QA frameworks to catch reward hacking and ensure environment quality. - Build interfaces that make collecting human data fast and painless for the people providing it. - Harden execution environments — sandboxing, snapshotting, tool coverage — so tasks hold up at training scale. - Embed with the teams and domain experts who use our systems day-to-day, and work with operations, security, and compliance partners to roll our systems out to new users and vendors. Minimum qualifications - A track record of owning major projects end-to-end in fast-paced, ambiguous environments — for example as a founder or CTO, forward deployed engineer, tech lead, founding engineer at a startup, or creator of a substantial open-source project. - Trusted to run key projects: you lead and inspire others, plan workstreams effectively, collaborate with cross-functional stakeholders, and proactively eliminate or escalate blockers. - Strong software engineering skills in at least one modern programming language — we mostly use Python and TypeScript, but care more that you pick new tools up quickly than that you know our exact stack. Familiarity with Docker, Kubernetes, and common cloud infrastructure is a plus. - Effective use of AI tools in your own day-to-day work. - Care about the societal impacts of your work. Preferred qualifications - Experience with reinforcement learning on LLMs, particularly on the data side: creating evals, environments, rewards, graders, or training data. - Experience helping organizations use AI more effectively, including integrating wit

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Security organization protects the models, the infrastructure, and the people behind them, spanning platform and application security, detection and response, identity, compliance, corporate engineering and IT, insider risk, and physical security. The adversaries are well resourced, the assets are novel, and the consequences of getting it wrong extend beyond Anthropic. As Technical Recruiter, Security, you'll join the small team of recruiters who hire for that organization, owning full lifecycle recruiting for your searches and partnering with security leaders to turn ambiguous needs into clear search strategies. Security professionals are among the most heavily recruited people in technology, and earning their attention takes real domain fluency rather than a template. Key responsibilities - Own full lifecycle recruiting for a portfolio of roles across the Security organization, from intake through offer and close - Run structured intakes with security hiring managers, translating ambiguous needs into scoped requirements, calibrated bars, and search strategies - Build and maintain pipelines of specialized security talent, with an emphasis on passive candidates - Refine security interview loops, take-home assignments, and scorecards alongside hiring managers, your recruiting counterparts, and Recruiting Operations - Develop genuine domain fluency so you can hold a credible conversation with a detection engineer, a cryptographer, and a compliance lead in the same week - Advise hiring managers with market data and candid calibration feedback, and influence decisions through credibility rather than volume - Partner with Compensation, People Partners, and Mobility to structure equitable offers and guide candidates to close - Handle sensitive role and candidate information with discretion, including for searches whose scope is confidential Minimum qualifications - Deep full lifecycle recruiting experience, with substantial time supporting security, infrastructure, or comparably technical engineering organizations - Ability to hold a substantive technical conversation about security domains such as application security, cloud and infrastructure security, detection and response, identity, or compliance, and to evaluate technical qualifications rather than match keywords - Proficiency with an applicant tracking system like Greenhouse and other modern sourcing tools - Experience partnering directly with hiring managers on intake, bar calibration, and interview loop design - Sound independent judgment on candidate quality, and the ability to redirect a hiring manager away from pedigree and credential proxies toward the underlying competencies - Genuine interest in Anthropic's mission and in the role a strong security function plays in achieving it Preferred qualifi

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking an experienced Finance Systems Integration Engineer to support our finance systems transformation at one of the fastest-growing AI companies. You'll design and build integrations connecting our ERP platform with critical financial applications and support our ERP implementation initiatives. As you master our integration landscape, you'll have opportunities to expand into Claude-powered AI automation and data pipeline development. You'll build the integration backbone for one of the fastest-growing AI companies, with a front-row seat to how Claude transforms financial operations. This is a foundational role where you'll shape our integration architecture from the ground up, then expand into cutting-edge AI automation as our needs evolve. You'll work alongside teams building frontier AI systems while directly applying that technology to solve real financial operations challenges. In this role you will: Core Focus: Integration Development & ERP Support - Design, build, and maintain integrations connecting ERP systems with downstream applications including ZipHQ, Brex, Navan, Clearwater, Payroll systems, Salesforce, and other critical financial platforms using Workato, MuleSoft, or similar iPaaS solutions - Support integration development and testing during the ERP implementation projects - Develop and maintain REST APIs, webhooks, and OAuth 2.0 authentication flows for secure system-to-system communication - Implement real-time and batch integration patterns supporting high-volume financial transactions - Establish monitoring, alerting, and error-handling frameworks to ensure integration reliability and data integrity - Document integration architectures, data flows, API specifications, and troubleshooting procedures - Collaborate with implementation consulting partners and vendors on technical integration requirements Additional Scope: AI Automation & Data Infrastructure As you master our integration landscape, you'll have opportunities to expand into: AI Agent Development - Build and deploy Claude-powered AI agents that automate financial operations including intelligent document processing, workflow automation, financial audit and reconciliations, and self-service reporting - Design agentic workflows that leverage Claude API capabilities integrated with ERP platform data and processes - Create automated validation and quality assurance processes for AI-generated outputs - Partner with Finance teams to identify automation opportunities and translate requirements into AI agent solutions Data Pipeline Support - Support data pipeline development using Airflow for workflow orchestration and dbt for data transformation - Build and maintain data flows from ERP and other financial systems into BigQuery for analytics and reporting - Implement data quality checks a

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the Child Safety team, you will be responsible for our child safety enforcement workflows, responsible for scaling, maintaining, and continuously improving the systems and processes we use to detect and respond to child sexual abuse material (CSAM) and child sexual exploitation material (CSEM) generated or facilitated through Anthropic's products. This is a deeply operational role. You will serve as the central point of contact for those who conduct content review, managing day-to-day workflows, quality assurance, and escalation processes to ensure reviews are accurate, consistent, and conducted with appropriate support structures in place. You will also work closely with internal Engineering, Policy, and Legal teams to scale detection systems and close enforcement gaps as the threat landscape evolves. This work is essential to Anthropic's mission. Child safety is one of our highest-priority harm areas, and the person in this role will have a direct and meaningful impact on protecting children from AI-facilitated exploitation and abuse. Important context for this role: In this position you will regularly be exposed to and engage with explicit content of a sexual nature involving minors, as well as content that may be violent or psychologically disturbing. Anthropic takes the wellbeing of team members working in this area seriously and provides access to wellness resources and support. Candidates should carefully consider this aspect of the role before applying. Key responsibilities - Own the day-to-day operational management of child safety content review workflows, including task routing, queue management, escalation handling, and SLA monitoring - Serve as the primary point of contact for review partners conducting child safety content review, including onboarding, training, quality assurance, and ongoing relationship management - Design and improve enforcement workflows to scale effectively as volume grows, while maintaining high accuracy and consistency across review decisions - Partner with Engineering and Data Science teams to optimize detection models and automated enforcement systems for CSAM, CSEM, and related child safety policy violations - Review novel or ambiguous flagged content to drive enforcement decisions and surface policy gaps to the Safeguards policy design team - Develop and maintain internal documentation, decision trees, and review guidelines that enable accurate and consistent enforcement at scale - Keep up to date with emerging AI policy enforcement best practices, evolving legal frameworks, and developments in child safety technology, and use these to inform our workflows - Identify and report trends in misuse patterns to internal stakeholders, including Policy, Legal, and Trust & Safety leadership - Coordinate reporting obligations to relevant external bodies (e.g., NCMEC) in accordance with applicable law and Anthropic policy Minimum qualifications - Experience in trust & safety, content moderation operations, or policy enforcement with direct exposure to child safety, CSAM/CSEM, or related child protection harm areas &

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for an Engineering Manager to lead the Interventions team: the group responsible for what happens when a safety system fires. It owns the composable arsenal of systems that sit between our detection stack (classifiers and probes) and the user, across every Anthropic surface: 1P products, the API, and third-party clouds. This includes inline interventions for areas like bio, cyber, and acceptable usage as well as downstream areas like child safety and copyright. This team is responsible for ensuring that we evolve and drive the quality of our interventions to enable our products to grow safely. Key responsibilities - Hands-on lead and grow a team of engineers; own roadmap, OKRs, and execution. - Drive cross-functional work with ML Infra, Research, Product, Policy, and Legal - and with cloud partners for 3P deployment. - Set the bar for when an intervention is good enough to ship - backed by measurement - and represent safety and product tradeoffs to leadership and external stakeholders. - Own production reliability for intervention and compliance systems: incident response, postmortems, SLOs, and the verification processes that prevent repeat incidents. Minimum qualifications - Have managed engineering teams shipping production ML or safety-enforcement systems where the system's decisions directly affected users. - Have run high-stakes, compliance-adjacent production systems: comfortable with on-call, incidents, regulator-driven requirements, and building the process scaffolding that prevents recurrence. - Care about measurement: you've built (or insisted on) the evals that prove a system does what it claims, and you've killed things that didn't. - Can drive ambiguous, multi-stakeholder tradeoffs (safety vs UX vs latency vs cost) to a decision and own the outcome. - Care deeply about AI safety and want your team's work to be the reason advanced models can be deployed at all. Preferred qualifications - Have worked in trust & safety, integrity, or abuse-prevention engineering at scale. - Experience with compliance-driven systems (child safety, copyright, age assurance) and the legal/policy interfaces they require. - Have shipped systems across multiple cloud providers and understand the parity/verification problems that creates. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 - $485,000 USD Logistics &lt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's Safeguards team is responsible for enforcing our policies, protecting users, and ensuring our platform is not misused. As a Safeguards Enforcement Analyst focused on Safety Evaluations, you'll play a central role in ensuring our models meet safety and policy standards before and after launch. You'll run and monitor evaluations, drive mitigations when issues surface, coordinate the creation of new evals, and help build the processes and documentation that allow the team to scale this work over time. This role requires someone who is detail-oriented, comfortable navigating ambiguity, and capable of coordinating across teams to break new ground and drive work to completion. This work is deeply cross-functional — you'll partner closely with policy experts, Safeguards engineering teams, and many other stakeholders throughout the organization to ensure our evaluations are comprehensive and current, and that findings translate into meaningful improvements to model behavior. Responsibilities - Support model launch readiness by running evaluations, monitoring and interpreting results, and surfacing regressions or unexpected behavior changes to relevant stakeholders - Partner closely with policy and domain experts throughout the evaluation lifecycle — from identifying risks and scoping the right evaluation approach, to coordinating creation of new evals and ensuring existing ones remain current with evolving policies, threat vectors, and model capabilities - Work with cross-functional stakeholders to help manage evaluation outcomes, including interpreting results and driving mitigations where needed - Think strategically about eval quality to build processes and eval paradigms that keep evaluations unsaturated, high-signal, and insightful as models improve - Build out processes and frameworks for creating product-specific evaluations as Anthropic's product surface area expands - Help design and scope tooling improvements that accommodate evolving eval needs and expand self-serve eval creation and iteration for non-technical users - Write and maintain rigorous documentation for evaluation creation, execution, and interpretation as the team builds out eval tooling and processes You may be a good fit if you: - Have experience in trust and safety, content operations, policy enforcement, or a related operational role at a technology company - Thrive in ambiguous, fast-moving environments — you're energized rather than frustrated when the path forward isn't clearly defined and you need to figure it out as you go - Have experience building processes, workflows, or programs from scratch (zero-to-one work), not just maintaining existing ones - Have strong program management instincts, naturally creating structure around complex, multi-stakeholder efforts by tracking timelines, dependencies, and deliverables to keep work on track - Are eager to expand your technical toolkit, including adopting internal tools and AI-assisted workflows (e.g., Claude Code) to accelerate your work - Can manage multiple concurrent workstreams across different domain areas without losing track of details — strong prioritization and cont

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Anthropic’s Research Tools team builds systems that support our large-scale, distributed finetuning runs and improve the productivity of researchers. As a manager, you’ll support a team of machine learning and distributed systems experts to make these systems and tools highly efficient, support fast iteration on model development and research, and evolve the infrastructure continuously to incorporate new research advances. Our Research Tooling sits at the intersection of almost every technical group at Anthropic. You’ll work with research teams to incorporate their innovations into our production finetuning pipeline, product teams to help us iterate quickly on customer-oriented model improvements, and infrastructure teams to make sure our training runs and data pipelines are as efficient as possible. About Anthropic: Anthropic is an AI safety and research company working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business, and product. Responsibilities: - Prioritize the team’s work in collaboration with the technical lead, research teams, and product teams to support fast iteration on research projects and training runs. - Design processes (e.g., postmortem review, incident response, on-call rotations) that help the team operate effectively. - Coach and support your reports to understand and pursue their professional growth. - Run the team’s recruiting efforts efficiently, ensuring we can grow as quickly as we need through a period of rapid growth. You may be a good fit if you: - Believe that advanced AI systems could have a transformative effect on the world and are interested in helping make sure that transformation goes well. - Are an experienced manager (at least 2 years) and actively enjoy people management. - Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you’ll need to understand (at a high level) to be effective. Strong candidates may also have: - Experience working with research teams, especially as part of a “research to production” pipeline - Strong people management experience: Coaching, performance evaluation, mentorship, career development - Strong project management skills: Prioritization, communicating across team/org boundaries - Experience recruiting for your team: Predicting staffing needs, designing interview loops, evaluating candidates, and closing them Deadline to apply: None. Applications will be reviewed on a rolling basis. <div cla

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Product Support Specialist, you’ll be at the front lines of safely delivering AI to the world by responding to, investigating, and tracking user needs in your day to day. Additionally, you’ll help us identify – and close – gaps in our team’s technical knowledge, provide high-touch support to strategic customers, and demonstrate deep care for how we systematically support customers at scale. Responsibilities - Become an expert in all Anthropic products - Respond to user support cases with a variety of complexity, from questions for individuals to complex API debugging for large businesses - Clearly and empathetically communicate with a wide range of user personas, context-switching between guiding executives in a high-touch model to assisting consumer users in a rapid pace - Manage on-call tasks for high-urgency user issues with extreme ownership - Prioritize critically and comfortably adapt to an ever-evolving product landscape - Operate in ambiguity, making informed decisions even in never-before-seen situations - Partner with engineers, teammates, and other internal stakeholders to diagnose and resolve user issues, both individually and at scale - Suggest and drive improvements to increase user satisfaction through support processes as well as own initiatives that increase efficiency and drive down contact rates - Uplevel our team’s technical knowledge by scoping gaps, working with cross-functional partners to deeply understand relevant nuances, and building resources that grow with our products Minimum qualifications - Several years of relevant experience in technical product support in a high growth tech company, including API debugging, preferably in a second tier, escalated, or priority support team - Are familiar with APIs and technical SaaS products and can deeply understand technical docs with ease - Have demonstrated an ability to thrive in fast-paced, reactive situations while meeting core support metrics targets (e.g. CSAT, SLA, etc.) - Possess strong user empathy and are expert in the lifecycle of a support case; you can read between the lines of a user’s question, put yourself in their shoes, and get at the heart of their needs for a speedy, satisfying resolution - Have crisp but kind written communication skills and a deep care for the details - Enjoy helping others learn about new features and complex concepts - Experience troubleshooting SSO, SAML, and OAuth authentication flows - Are persistent and curious; you delight in the hunt of tracking down a bug or issue, and are energized by fixing this for all similar users going forward - Have experience contributing to the foundations of a support team – this is essential, highly valuable, but often unglamorous work <li clas

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking a talented and driven Workday Business Systems Analyst to join our People Systems team. You'll own the technical configuration, testing, and operational excellence of our Workday HRIS across two domains: PATT and HCM. Your deepest work will be on the PATT side, where you'll refine our existing payroll, absence, and time tracking configuration and shape PATT design decisions as they're made. On the HCM side, you'll own core HCM data structures, business process frameworks, and the security model that underpins everything we do in Workday. You'll be relied on as a system expert for both strategic guidance and hands-on delivery. This role is about moving the team forward, not just keeping the system running. The right candidate is passionate about where AI and internal tooling can make People Systems more effective, and treats "the way it's always been done" as a starting point to question rather than a constraint. We're looking for someone who is naturally curious and an exceptional problem solver — the kind of person who looks beyond the obvious or "standard" Workday answer and asks why before how. You'll find success in this role if you thrive in a fast-paced, high-growth environment and know how to reprioritize without losing rigor. You'll partner across many parts of the business, from the broader People team to Finance, IT, and beyond, to make sure our HRIS is secure, scalable, and a true business enabler. Responsibilities PATT and HCM - Configure and maintain Payroll: pay components, earnings and deductions, pay groups, period schedules, and payroll-related business processes - Configure and maintain Absence: time-off plans, accrual rules, eligibility criteria, and leave types - Configure and maintain Time Tracking: time entry templates, validations, work schedules and calendars, and overtime calculations - Configure and maintain Core HCM foundations: supervisory organizations, staffing models, job profiles and job/compensation structures, custom organizations, and worker data integrity - Support annual and recurring People cycles in Workday, including compensation review setup, open enrollment configuration, and org restructures (mass supervisory org changes and job catalog updates) - Design, build, and maintain business process definitions in both domains, including condition rules, calculated fields, custom validations, routing and approval logic, and notifications - Partner with the Payroll team to troubleshoot configuration-driven payroll issues, including gross-to-net discrepancies, retro calculations, and off-cycle errors — the Payroll team owns processing; you own the configuration behind it - Bring a strong command of the Workday security model: role-based, user-based, and intersection security groups, domain security policies, business process security policies, and integration system users (ISUs), with sound judgment about when to leverage each as you configure and troubleshoot across domains - Support security and data audits in partnership with the broader team, using Workday delivered and custom audit reports to analyze access patterns, remediate exceptions

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As Commercial Counsel for Platform & Marketplace at Anthropic, you'll support scaling up go-to-market motions and platforms like the Claude Marketplace, which lets enterprise customers discover, buy, and pay for third-party applications. You'll be the trusted legal partner to Business Development teams within Anthropic’s Partnerships & Alliances org, shaping how we collaborate with sellers and customers on existing and future platforms. You’ll not only focus on how we interact with our own resale channels but also on how we participate in third-party marketplaces. We'll count on you to own, negotiate, and continuously improve the core contracting vehicles for these go-to-market programs, as well as supporting terms that sit between sellers and buyers. Key responsibilities - Own end-to-end legal strategy and execution for certain partnership ecosystems and contracting programs - Serve as one of the legal partners to our Partnerships & Alliances business team, functioning as a strategic advisor embedded in partnership planning - Independently lead complex, multi-party negotiations involving technical integrations, revenue-sharing arrangements, joint go-to-market strategies, and strategic commitments that may implicate other Anthropic business relationships - Architect scalable partnership frameworks, templates, and programs that enable the broader organization to execute deals efficiently while maintaining appropriate risk controls - Provide strategic counsel on partnership structures that balances legal risk management with aggressive growth objectives - Coordinate cross-functionally with Compute, Strategic Pursuits, Finance, and GTM teams on deals where partnership terms interact with other commercial relationships and commitments Minimum qualifications - JD and active membership in at least one U.S. state bar (California preferred) - Demonstrated track record of independently leading complex, multi-stakeholder negotiations with major technology companies that resulted in successful partnership launches, including situations where Anthropic's interests must be balanced against partners and end customers simultaneously - Experience serving as the go-to legal partner for a partnerships or business development organization; the attorney that business leaders actively want in strategy sessions - Deep understanding of partnership economics: how deal registration works, why revenue attribution matters to partners, how to structure incentives that align interests, and what motivates a partner to prioritize one vendor over another - Superior judgment in risk assessment and strategic tradeoffs, with the confidence to recommend which partnerships to pursue, which terms are worth fighting for, and when to walk away - Outstanding communication skills with executive presence;

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Transformative AI Research Economist at Anthropic, you will build macroeconomic models of AI that could be genuinely transformative and develop the scenario-based forecasting tools that let us reason quantitatively about economic trajectories with no historical precedent. You will work on questions of aggregate growth, income distribution, and economic governance under scenarios that most of the profession has not yet modeled seriously. You will ground projections in microeconomic signals from the Anthropic Economic Index — usage patterns across millions of real-world AI interactions, surfaced through privacy-preserving measurement — so that scenario forecasts are disciplined by what we actually observe about task transformation and productivity. You will use frontier methods in growth theory, computational macro, and structural estimation, and contribute to AI-powered tools that expand what economic research can do. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system , we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Responsibilities - Build macroeconomic models of transformative AI spanning growth, labor markets, and income distribution - Develop and maintain scenario-based forecasting tools; publish forecasts for GDP, productivity, and unemployment under a range of AI-capability trajectories - Ground macroeconomic projections in microeconomic data from the Anthropic Economic Index, constraining theory with observed patterns of adoption and task transformation - Analyze questions of income distribution and economic governance under transformative-AI scenarios - Contribute to the development of AI-powered research tools for economics - Contribute to Economic Index Reports and publish Research Briefs on first-order questions as they arise - Build and maintain relationships with academic institutions, policy think tanks, and other research partners - Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders You May Be a Good Fit If You Have - PhD in Economics, or an exceptional candidate close to completion -

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Technical Program Manager for Inference, you'll be the critical bridge between our inference systems and the broader organization. You'll drive strategic initiatives across inference runtime and accelerator performance—coordinating model launches, managing cross-platform dependencies, and ensuring reliability across multiple hardware targets. This role is essential for keeping our most contended infrastructure teams shipping effectively while Research, Product, and Safety all depend on their output. Responsibilities: - Systems Integration & Coordination : Lead cross-functional initiatives for new infrastructure integration, establishing clear ownership, timelines, and communication channels between teams. Drive end-to-end planning for major infrastructure transitions including platform modernization and new tech adoption. - Performance & Efficiency: Partner with engineering teams to identify optimization opportunities, track performance metrics, and prioritize work that unlocks capacity gains. Coordinate across runtime and accelerator layers to ensure efficiency wins ship without compromising reliability. - Launch Coordination: Drive end-to-end readiness for model and feature launches across multiple hardware platforms. Establish processes for cross-platform validation, manage launch timelines, and ensure smooth handoffs between runtime, accelerator, and downstream teams. - Strategic Planning: Own and prioritize the inference deployment roadmap, working closely with engineering leadership to prioritize initiatives and manage dependencies. Provide visibility into upcoming changes and their organizational impact. - Stakeholder Communication: Build strong relationships across research, engineering, and product teams to understand requirements and constraints. Translate technical complexities into clear updates for leadership and ensure alignment on priorities and timelines. - Process Improvement: Identify inefficiencies in current workflows and drive systematic improvements. Establish metrics and dashboards to track infrastructure health, capacity utilization, and deployment success rates. You may be a good fit if you: - Have several years of experience in technical program management, with proven success delivering complex infrastructure programs, preferably in ML/AI systems or large-scale distributed systems - Have deep technical understanding of inference systems, compilers, or hardware accelerators to engage substantively with engineers and identify technical risks. - Excel at creating structure and processes in ambiguous environments, bringing clarity to complex cross-team initiatives - Have strong stakeholder management skills and can build trust with both technical and non-technical partners - Are comfortable navigating competing priorities and using data to drive technical decisions - Have experience with infrastructure s

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As Anthropic scales its customer base across Claude Enterprise, Claude Code, and our API, we need to extend world-class customer success to a broader segment of customers through innovative, scalable approaches. The Scaled CSM will pioneer digital-first and one-to-many customer engagements that drive adoption, stickiness, retention, and expansion at scale. This role sits at the intersection of Customer Success innovation and AI transformation. As a Scaled Customer Success Manager at Anthropic, you'll be owning the success of a large portfolio of Commercial and Enterprise customers, you’ll design and execute scalable customer journeys through digital touch points, automated programs, one-to-many engagements, and strategic human intervention. You won't just manage customers — you'll "Claudify" the customer experience by building AI-powered processes that transform how customers adopt and derive value from Claude. Your work will directly shape how we engage customers at scale while maintaining the personalized, high-value experience that defines Anthropic. You'll collaborate closely with our Programmatic Success team to develop compelling customer content, with Sales organization to co-develop strategic plans, ensure seamless handoffs, and drive growth opportunities, with Product to channel customer insights and build consumption-driving features, and with Customer Success leadership to continuously optimize our scaled engagement model, all while pioneering how we leverage our own AI capabilities to transform digital customer engagement. Responsibilities: - Own scaled customer engagement for a large portfolio of Commercial and Enterprise accounts, managing customers through timebound, digital-first touchpoints that drive activation, consumption, retention, and expansion across Claude Enterprise, Claude Code, and API products - Execute timebound strategic human touchpoints at key moments— customer activation, expansion discussions, renewal conversations, risk interventions - ensuring high-impact interactions when customers need them most - Provide technical guidance. Develop deep product expertise to guide implementation decisions, advise on safe, impactful adoption of new features, , and translate AI capabilities into business value for audiences from developers to executives - Channel customer voice back to Product and leadership by aggregating insights from digital interactions, surveys, and community engagement to influence roadmap and improve customer experience - Partner cross-functionally with Marketing on customer campaigns, Sales on handoffs and growth, Product on adoption-driving features, and Customer Success on playbook development and optimization - Triage and prioritize across a pooled book. Work from a shared queue of engagement requests across a large customer pool. Ramp quickly on unfamiliar accounts, ruthlessly prioritize through a business-impact lens, and maintain quality across high concurrent volume.&lt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Our mission on the Connectivity team is to make Claude the most connected AI. As agents take on more real-world work, we're taking a leading role in defining how they get access to external systems — safely, with the right permissions, and in ways enterprises can trust. We ship for claude.ai , Claude Code, Cowork, and the API. We own the MCP proxy that routes every tool call and the OAuth and token management that keeps connections authenticated. We're also core contributors to the MCP spec — now an open standard under the Linux Foundation — and maintain the official Python and TypeScript SDKs. We're looking for an experienced engineering leader to lead a team of Connectivity engineers based in London. The Connectivity team spans San Francisco and London, and you'll work closely with engineering leadership and partner teams in San Francisco to set direction and deliver together across both sites. You'll lead a team working on problems where reliability and enterprise trust are the bar: token refresh at scale, admin controls that let IT govern what agents can do, and proxy infrastructure that stays up when partner servers don't. Key responsibilities - Lead a team of engineers building the connectivity infrastructure that powers tool use across Anthropic's product suite, from the MCP proxy to OAuth and token management - Take an inclusive, equitable approach to hiring and coaching top technical talent, and maintain a high-performing team - Coach, mentor, and provide career development guidance to your direct reports, helping them set and achieve their professional goals - Partner with Connectivity engineering leadership in San Francisco, along with product, security, and platform teams, to define the team's roadmap and create clarity for the team in an ambiguous and evolving environment - Drive cross-team and cross-org alignment to ship work that spans claude.ai , Claude Code, Cowork, and the API, working effectively with teams primarily based in the US - Establish and drive adoption of engineering best practices within your team, including the operational rigor (on-call, incident response, postmortems) required for infrastructure that other teams and external partners depend on - Contribute to engineering-wide initiatives as a member of Anthropic's engineering management team Minimum qualifications - Experience managing software engineering teams, including hiring, coaching, and performance management - A technical background in backend or platform engineering, with the depth to guide architectural decisions and engage credibly in technical discussions - Experience operating production distributed systems, with an understanding of what reliability, observability, and incident response require at scale - Excellent communication skills, with the ability to build consensus across teams and ti

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are looking for a Technical Cyber Threat Investigator to join our Threat Intelligence team. In this role, you will be responsible for detecting, investigating, and disrupting the misuse of Anthropic's AI systems for malicious cyber operations. You will work at the intersection of AI safety and cybersecurity, conducting thorough investigations into potential misuse cases, developing novel detection techniques, and building robust defenses against emerging cyber threats in the rapidly evolving landscape of AI-enabled risks. Your work will directly protect the broader ecosystem from sophisticated threat actors who seek to leverage AI technology for harm. Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. Responsibilities - Detect and investigate attempts to misuse Anthropic's AI systems for cyber operations, including influence operations, malware development, social engineering, and other adversarial activities - Develop abuse signals and tracking strategies to proactively detect sophisticated threat actors across our platform - Create actionable intelligence reports on new attack vectors, vulnerabilities, and threat actor TTPs targeting LLM systems - Conduct cross-platform threat analysis grounded in real threat actor behavior, using open-source research, dark web monitoring, and internal data - Utilize investigation findings to implement systematic improvements to our safety approach and mitigate harm at scale - Study trends internally and in the broader ecosystem to anticipate how AI systems could be misused, generating and publishing reports - Build and maintain relationships with external threat intelligence partners, information sharing communities, and government stakeholders - Work cross-functionally to build out our threat intelligence program, establishing processes, tools, and best practices You may be a good fit if you - Have demonstrated proficiency in SQL and Python for data analysis and threat detection - Have experience with large language models and understanding of how AI technology could be misused for cyber threats - Have subject matter expertise in abusive user behavior detection, such as influence operations, coordinated inauthentic behavior, or cyber threat intelligence - Have experience tracking threat actors across surface, deep, and dark web environments - Can derive insights from large datasets to make key decisions and recommendations - Have experience with threat actor profiling and utilizing threat intelligence frameworks (MITRE ATT&CK, etc.) - Have strong project management skills and ability to build processes from the ground up - Possess excellent communication skills to collaborate with cross-functional teams and present to leadership Strong candidates m

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic launches products at lightning speed and many of them grow at an unprecedented pace, too. For no product is this more true than Claude Code, the fastest-growing software product in history. That said, speed of adoption is not the same as depth of adoption. We’re building a team of Technical Specialists to drive meaningful adoption breadth and depth in our most strategic customers. We’ll do this through delivery of high-quality technical engagement and enablement in the customer’s ~ 90 days before and after contract signature. As a Technical Specialist, you’ll largely engage with customers post-sale. Once an account’s implementation set-up is complete, you’ll convert bottom-up developer passion into org-wide meaningful adoption through bespoke enablement tailored to the customer's stack, repos, and workflows and focused upon deep adoption of proprietary Claude capabilities, which we know drive stickiness. You'll also engage in strategic pilots before signature — partnering with Sales, Applied AI, and the customer's engineering leads to scope the pilot, run the enablement, and instrument the success criteria that close the deal. Carrying that context from pilot into post-sale is what makes adoption stick. This is not a technical implementation role — that work sits with our Implementation Specialists. You'll spend your time in front of developers launching Claude Code, department leaders adopting Cowork, on stage at customer events and Anthropic builder summits, and in Claude Code and Cowork, building the demo apps and reference implementations that prove what's possible. You’re the kind of person engineers want to grab coffee with after your workshops — credible because you can open a terminal in the meeting and actually drive the tool, exciting because you've thought hard about how agentic AI changes how software gets built, and useful because you can answer the next three questions a senior platform engineer is about to ask about security, scale, or agent behavior. What You'll Do: Drive end-user excitement inside enterprise accounts (primary focus) - Design and deliver customer-specific enablement programs — workshops, office hours, "build your first agent" labs, role-based curricula for engineering, data, platform, security, and knowledge-worker audiences - Drive deep adoption of proprietary Claude Code capabilities that make our tools sticky (subagents, hooks, MCP servers, headless mode, managed settings) tailored to the customer's stack, repos, and actual workflows (CI/CD, IDE integration, source control, secure coding, agentic pipelines) - Enable and excite champions and AI Center of Excellence leads inside customer orgs, arming them to scale the motion without you in the room Support strategic pilots with pre-sales technical enablement - Partner with Account Executives, Applied AI, and customer engineering leads on pilots for strategic accounts - Carry pilot context into post-sale engagement so the customer’s experi

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As the Recruiting Solutions Engineer dedicated to Recruiting at Anthropic, you will be the trusted technical partner helping recruiters build with Claude as we transform how Anthropic hires. The role spans three connected lanes — education, technical support, and building — in that order. Your first mission is helping recruiters help themselves: finding the AI skills and workflows our strongest recruiters have already invented, codifying them, and teaching them at scale. Where self-serve runs out, you provide hands-on technical support. And where the same need keeps surfacing, you build fast pilots that prove the workflow. Working closely with Recruiting leadership, People Products Engineering, and Data Solutions, you'll own the full enablement loop: you'll leverage your AI engineering expertise to turn recruiter-built skills into reusable assets, design evaluation approaches for AI-assisted hiring workflows, and create the technical resources that let a recruiting org operate at the frontier of AI. Key responsibilities - Serve as the dedicated technical advisor to the Recruiting organization — embedded with recruiters, sourcers, and coordinators to expand what's possible with Claude in real hiring workflows - Lead with education: identify and codify the skills and workarounds recruiters have created, turn them into teachable and reusable assets, and run the enablement motion (sessions, office hours, workshops) that scales them across the org - Work hands-on with recruiters: pairing on prompts, skills, and agent workflows; debugging where things break; turning support patterns into documentation so the same question isn't answered twice - Develop fast prototypes and pilots for high-value workflows that education alone can't solve — built scrappy, validated with real recruiter usage, and designed from day one with a graduation path into People Products' production stack - Collaborate closely with our internal AI governance group (the AI Council) to vet recruiter-built skills into shared tooling, and with People Products to hand off pilots that earn productionization - Identify patterns across teams and engagements, and contribute insights back to Recruiting leadership, Data Solutions, and People Products - Create technical content for recruiting audiences: documentation, tutorials, sample skills, and walkthroughs that assume curiosity rather than an engineering background - Foster community engagement through internal hackathons, demo sessions, and technical office hours Minimum qualifications - Experience as a Software Engineer, Forward Deployed Engineer, Solutions Engineer, or in a technical enablement role — or equivalent builder credibility from shipping real products - Production experience building LLM-powered applications and workflows, including prompting, context engineering, agent architectures, and evaluation - Strong programming sk

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Full-Stack Software Engineer in RL, you'll build the platforms, tools, and interfaces that power environment creation, data collection, and training observability. The quality of Claude's next generation depends on the quality of the data we train it on — and the systems you build are what make that data possible. You'll own product surfaces end-to-end — from backend services and APIs to the web UIs that researchers, external vendors, and thousands of data labelers use every day. You don't need a background in ML research. What matters is that you can take an ambiguous, high-stakes problem and ship a polished, reliable product against it, fast. This team moves very quickly. Claude writes a lot of the code we commit, which means the bottleneck isn't typing — it's judgment, taste, and the ability to react to what researchers need next. You'll iterate on data collection strategies to distill the knowledge of thousands of human experts around the world into our models, and you'll do it in a loop that closes in hours and days, not quarters or months. Anthropic's Reinforcement Learning organization leads the research and development that trains Claude to be capable, reliable, and safe. We've contributed to every Claude model, with significant impact on the autonomy and coding capabilities of our most advanced models. Our work spans teaching models to use computers effectively, advancing code generation through RL, pioneering fundamental RL research for large language models, and building the scalable training methodologies behind our frontier production models. The RL org is organized around four goals: solving the science of long-horizon tasks and continual learning, scaling RL data and environments to be comprehensive and diverse, automating software engineering end-to-end, and training the frontier production model. Our engineering teams build the environments, evaluation systems, data pipelines, and tooling that make all of this possible — from realistic agentic training environments and scalable code data generation to human data collection platforms and production training operations. What You'll Do - Build and extend web platforms for RL environment creation, management, and quality review — including environment configuration, versioning, and validation workflows - Develop vendor-facing interfaces and tooling that let external partners create, submit, and iterate on training environments with minimal friction - Design and implement platforms for human data collection at scale, including labeling workflows, quality assurance systems, and feedback mechanisms that surface reward signal integrity issues early - Build evaluation dashboards and observability UIs that give researchers real-time insight into environment quality, training run health, and reward hacking - Create backend services and APIs that connect environment authoring tools, data collection systems, and RL training infrastructure - Build and expand scalable code data generation pipelines, producing diverse programming tasks with robust reward signals across languages and difficulty levels - Develop onboarding automation and documentation tooling so new vendors and internal users r

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with. You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models. Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends. Responsibilities: - Implement and optimize post-training techniques at scale on frontier models - Conduct research to develop and optimize post-training recipes that directly improve production model quality - Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation - Develop tools to measure and improve model performance across various dimensions - Collaborate with research teams to translate emerging techniques into production-ready implementations - Debug complex issues in training pipelines and model behavior - Help establish best practices for reliable, reproducible model post-training You may be a good fit if you: - Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities - Adapt quickly to changing priorities - Maintain clarity when debugging complex, time-sensitive issues - Have strong software engineering skills with experience building complex ML systems - Are comfortable working with large-scale distributed systems and high-performance computing - Have experience with training, fine-tuning, or evaluating large language models - Can balance research exploration with engineering rigor and operational reliability - Are adept at analyzing and debugging model training processes - Enjoy collaborating across research and engineering disciplines - Can navigate ambiguity and make progress in fast-moving research environments Strong candidates may also: - Have experience with LLMs - Have a keen interest in AI safety and responsible deployment We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role. The annual com

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team We are seeking passionate Research Scientists and Engineers to join our growing Pre-training team in Zurich. We are involved in developing the next generation of large language models. The team primarily focuses on multimodal capabilities: giving LLMs the ability to understand and interact with modalities other than text. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Responsibilities In this role you will interact with many parts of the engineering and research stacks. - Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development - Independently lead small research projects while collaborating with team members on larger initiatives - Design, run, and analyze scientific experiments to advance our understanding of large language models - Optimize and scale our training infrastructure to improve efficiency and reliability - Develop and improve dev tooling to enhance team productivity - Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications & Experience We encourage you to apply even if you do not believe you meet every single criterion. Because we focus on so many areas, the team is looking for both experienced engineers and strong researchers, and encourage anyone along the researcher/engineer spectrum to apply. - Degree (BA required, MS or PhD preferred) in Computer Science, Machine Learning, or a related field - Strong software engineering skills with a proven track record of building complex systems - Expertise in Python and deep learning frameworks - Have worked on high-performance, large-scale ML systems, particularly in the context of language modeling - Familiarity with ML Accelerators, Kubernetes, and large-scale data processing - Strong problem-solving skills and a results-oriented mindset - Excellent communication skills and ability to work in a collaborative environment You'll thrive in this role if you - Have significant software engineering experience - Are able to balance research goals with practical engineering constraints - Are happy to take on tasks outside your job description to support the team - Enjoy pair programming and collaborative work - Are eager to learn more about machine learning research &l

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a member of the National Security Policy team at Anthropic, you will work directly with our most strategic national security customers and partners to drive transformational AI adoption. You will leverage your technical skills to architect innovative solutions that address our customers' business needs, meet their technical requirements, and provide a high degree of reliability and safety. In collaboration with the Sales, Product, Research, and Engineering teams, you’ll help national security partners develop strategies and implementation plans to integrate leading-edge AI systems into their mission. You will employ your excellent communication skills to explain and demonstrate complex solutions persuasively to technical and non-technical audiences alike. You also will play a critical role in identifying opportunities to innovate and differentiate our AI systems, while maintaining our best-in-class safety standards. We expect our team members to operate autonomously, thrive under ambiguity, and represent Anthropic at the highest level in customer environments. Core Responsibilities: - Act as a primary technical advisor for senior government leaders and prospective National Security customers evaluating Claude. Demonstrate how Claude can support U.S. and democratic allies’ national security operations and address customer use cases through proofs of concept. Provide technical guidance on integration, deployment, and adoption best practices. - Partner closely with the policy team and sales account executives to understand customer requirements. Develop customized pilots and prototypes, as well as evaluation suites to make the case for customer adoption. - Drive technical decision making by partnering on optimal setup, architecture, and integration of Claude into the customer's existing infrastructure. Demonstrate solutions to technical roadblocks. - Act as the voice of our customers and a key collaborator with our Product and Research teams to ensure we are delivering critical capabilities to the National Security community. - Travel to customer sites for senior leader meetings, AI implementation, technical enablement, and building relationships. - Establish a shared vision for creating solutions that enable beneficial and safe AI - Lead the vision, strategy, and execution of innovative solutions that leverage our latest models’ capabilities. You may be a good fit if you have: - Active TS/SCI security clearance (required) - 2+ years of experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Platform Engineer within the National Security space - Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include senior executives, engineering & IT teams, and more - Experience in the defense, technology, or cybersecurity industries - <p&g

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Enforcement Analyst, you will be responsible for reviewing content and executing enforcement actions across our products and services, with a focus on detecting and mitigating attempts to misuse Anthropic's AI systems for malicious cyber operations. Your initial focus will center on reviewing flagged activity related to cyberattacks, malware development, and offensive exploitation; however, this position may later expand to include broader areas of enforcement. Safety is core to our mission, and you'll help uphold policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a violent, technical, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. Key responsibilities - Review flagged content and accounts to make accurate, well-documented enforcement decisions in line with our usage policies - Detect and mitigate potential misuse of AI systems to facilitate cyberattacks, malware creation, exploitation tooling, and related harmful cyber operations - Triage and escalate novel, ambiguous, or high-severity cases to appropriate stakeholders - Provide detailed feedback to the Safeguards policy design team on policy gaps surfaced through real enforcement scenarios - Partner with Engineering and Data Science teams by surfacing detection model errors and quality signals from review to improve precision and recall - Maintain high accuracy and consistency standards across review queues - Keep up to date with emerging AI policy enforcement best practices, threat actor tactics, and the evolving cyber threat landscape, using these to inform enforcement decisions Minimum Qualifications - Experience in cybersecurity, including knowledge of offensive techniques, exploit development, malware analysis, or vulnerability research - Experience performing content review, abuse investigations, or policy enforcement at volume - Proficiency in SQL and/or Python for data analysis and threat detection - Experience identifying emerging risks and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams - Experience working with generative AI products, including writing effective prompts for content review and enforcement Preferred qualifications - Experience in trust & safety, abuse investigations, cybersecurity investigations, or threat intelligence in a technology or AI company - Experience with large language models and an understanding of how AI technology could be misused for cyber operations - Experience operating within abuse monitoring programs or enforcement review systems - Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space - Experience working with government agencies,

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for a threat intel manager to build and run our CBRN-E & Advanced Weapons team within Threat Intelligence. This team detects, investigates, and disrupts attempts to misuse Anthropic's AI systems for chemical, biological, radiological, nuclear, and explosives threats and for the development of advanced or novel weapons. You will mature this from a promising start into a rigorous program, hiring investigators with real CBRN-E, weaponization, and counterproliferation expertise, sharpening detection beyond broad harm screens into threat-specific capabilities, and personally leading the cases where scientific judgment determines whether we're seeing curiosity, legitimate research, or a genuine weapons-development attempt. The area carries significant engagement with government, biosecurity, and scientific stakeholders. Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. Key responsibilities - Own strategy, priorities, and outcomes for the CBRN-E & Advanced Weapons mission area; mature it from an emerging function into a rigorous investigative program - Hire, manage, and develop a team of investigators with deep domain expertise across biological, chemical, and weapons-development threat areas - Personally lead investigations into attempts to use our systems to develop, enhance, or disseminate CBRN-E weapons, or advanced weapons capabilities - Evolve detection from broad harm screens toward CBRN-specific signals and methodologies tailored to dual-use research concerns, in partnership with our collections engineers - Set the analytic quality bar: cross-platform threat analysis grounded in real threat actor behavior, open-source research, and publicly reported weapons programs - Own escalation and enforcement decisions with policy and enforcement teams for the highest-severity misuse category we handle - Lead external engagement with government agencies, biosecurity and chemical-security research communities, and scientific organizations - Inform safety-by-design and capability-evaluation strategies by forecasting how threat actors will leverage frontier AI for CBRN-E purposes - Serve as a liaison to government partners, educating stakeholders on AI-enabled threats through regular reporting and briefings. Minimum qualifications - Are an intelligence analyst, policy expert, or researcher with deep domain expertise in biosecurity, chemical defense, weapons non-proliferation, dual-use research of concern (DURC), or related CBRN-E threat domains - Have led investigative or analytic teams and are a senior domain expert with demonstrated mentorship and program-building experience ready to lead - Have experience with threat actor profiling,threat intelligence analysis frameworks, and collection frameworks - Have hands-on experience with large language models and how AI cou

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Regional Research Economist at Anthropic, you will work to collaborate with governments, academia, industry, and civil society in your region to measure and understand AI's effects on the economy and explore research-driven policy interventions. You will contribute to the development of the Anthropic Economic Index and its extension to generate regionally-relevant insights, establish new methodologies to measure the usage, diffusion, and impact of AI throughout the economy, and work to broaden access to and usage of the insights generated by the Index. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Key responsibilities - Build and maintain relationships with academic institutions, policy think tanks, and other research partners as the primary point of contact for these organizations on economic impact work in your region - Advance research collaborations that answer country- or regional-specific economic impact questions - Translate research insights into actionable recommendations for policy discussions - Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including country/regional-specific analysis - Design and collaborate on empirical research on AI's economic effects with governments, academia, industry, and civil society in your region - Develop new methodological approaches, in collaboration with partners in your region, for studying AI's impact on: - Labor markets and the future of work - Productivity and task transformation - Economic inequality and displacement - Industry-specific disruption and adaptation - Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios - Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection - Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders Minimum qualifications - PhD in Economics - Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning <li&gt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Research Engineer on the Economic Research Data Platform team, you will design, build, and maintain critical infrastructure that powers Anthropic's research on AI's economic impact. You will work with data systems from across Anthropic, including our research tools for privacy-preserving analysis. The Economic Research team is part of the Anthropic Institute , and studies the economic implications of AI on individual, firm, and economy-wide outcomes. We build scalable systems to monitor AI usage patterns and directly measure the impact of AI adoption on real-world outcomes. We publish research and data, including the Anthropic Economic Index, for the benefit of the public – helping policymakers, businesses, and workers understand and navigate the transition to powerful AI. The questions we work on include: how is AI changing jobs and economic activity, who is adopting it and why, and what determines whether a region or industry captures value from it. In this role, you will work closely with teams across Anthropic — including Data Science and Analytics, Data Infrastructure, Societal Impacts, and Public Policy — to build scalable and robust data systems that support high-leverage, high-impact research. Strong candidates will have a track record building data processing pipelines, architecting and implementing high-quality internal infrastructure, working in a fast-paced environment, and navigating ambiguity. Responsibilities : - Build and operate the data pipelines that turn raw usage data into clean, reusable, privacy-preserving datasets - Design new systems - including developing classifiers, training probes on model internals, and building the ML pipelines behind them — for understanding how Claude is used and the impact it's having on the economy - Build self-serve workflows to ingest and integrate external data sources so they're interoperable with internal datasets - Develop the APIs, libraries, and interfaces that serve data to researchers and the public - Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic's safety mission - Contribute to the team roadmap, documentation, and practices that enable self-serve data access while maintaining safety and governance standards - Ensure data reliability, integrity, and privacy compliance across all economic research data infrastructure You might be a good fit if you: - Have significant experience building data-intensive applications, pipelines, or internal tooling in production - Have experience with cloud infrastructure platforms such as AWS or GCP, and take pride in writing clean, well-documented code in Python that others can build upon - Have intuition for analytics workflows and empathy for how researchers and data scientists work - Are comfortable making technical decisions with incomplete information while keeping engineering standards high &l

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the RL Teams Our Reinforcement Learning teams play a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of our latest Claude models. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to write, edit, test, debug, and ship real software — end to end, on real codebases, with real tools — and to do it correctly, fast, and safely. This role blends research and engineering. You'll design RL environments and coding tasks, build the reward signals and verifiers that capture what "good code" means, run training experiments on frontier models, diagnose why a model does (or doesn't) get better at a class of software-engineering work, and improve the speed and reliability of the pipelines that make all of that iterate fast. Code RL spans several focus areas — from agentic coding behaviors and code correctness, to long-horizon autonomous engineering, to high-performance code for accelerators — and we'll match you to the area where you'll have the most impact. You may be a good fit if you: - Have strong software-engineering skills and deep Python expertise, including async/concurrent programming - Are comfortable owning systems end to end and debugging across the stack - Can balance research exploration with engineering implementation, and engage rigorously in shaping experimental design and interpreting results - Care about code quality, testing, and performance - Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems Strong candidates may also have: - Experience with reinforcement learning, RLHF, post-training, or LLM finetuning - Built coding agents, code-execution sandboxes, eval harnesses, veri

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: - Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability - Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure - Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance - Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams - Build and maintain production logging, monitoring dashboards, and evaluation infrastructure - Add new capabilities to the training codebase, such as long context support or novel architectures - Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams - Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned You May Be a Good Fit If You: - Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems - Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other - Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure - Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs - Excel at debugging complex, ambiguous problems across multiple layers of the stack - Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents - Are passionate about the work itself and want to refine your craft as a research engineer - Care about the societal impacts of AI and responsible scaling Strong Candidates May Also Have: - Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale - Contributed to open-source LLM frame

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic publishes risk reports: long-form technical documents laying out our assessment of the most serious potential risks from our models in domains like CBRN, cyber operations, and AI autonomy, along with the evaluation results behind that assessment, the safeguards we've applied, and our reasoning for why a given model is safe to deploy under our Responsible Scaling Policy. Some risk reports are standalone periodic assessments; others are more targeted, produced when we release a specific frontier model. These are some of the most consequential documents we produce, and one of the main ways we hold ourselves publicly accountable for the safety claims we make. We're hiring a Research Operations Specialist to own risk report operations. You'll be embedded with safety and research teams through each report cycle: coordinating contributions from dozens of researchers, holding the schedule and the open-threads list, and making sure the document ships on time as a single, internally consistent whole. You'll also do substantive editorial work, turning evaluation results, threat models, and researcher notes into clear prose and pushing back when a safety argument doesn't hold together. Risk reports sit within a wider family of external safety artifacts, including system cards and Responsible Scaling Policy updates. Part of this role is keeping those documents consistent with each other so that what we commit to in one place matches what we commit to and deliver on everywhere else. This role sits in Research Operations and works closely with our Frontier Red Team, Safeguards, Alignment, and capabilities researchers. The job is part project management, part translation: keeping a complex, many-author, hard-deadline document on track while making frontier risk assessment legible to researchers, policymakers, journalists, and the public without losing precision. Key responsibilities - Drive risk report production end to end: own the timeline, the contributor list, and the open-threads tracker - Coordinate core contributors across Frontier Red Team, Safeguards, Alignment, Interpretability, and capabilities research; chase drafts, resolve disagreements, find ground truth, and run the final polish pass - Edit (and sometimes write) content; work with researchers and red-teamers to turn evaluation results, threat models, and plots into clear, non-marketing prose, and keep Anthropic's voice consistent across sections drafted by many different people - Guard accuracy and consistency: catch terminology drift, risk claims that subtly contradict each other, and gaps between internal findings and what the draft says - Keep the risk report aligned with system cards, RSP disclosures, and other safety documentation, and flag conflicts early - Improve the process between reports; build templates, style guidance, and contributor checklists so each cycle starts from a stronger baseline - Pick up other research-adjacent operations and writing work related to our external artifacts and Anthropic's RSP Minimum qualifications - Demonstrated technical writing ability: can take dense, jargon-heavy source

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI Security Architect, you will serve as Anthropic's trusted security expert for our most demanding enterprise customers. You'll engage directly with CISOs, security architects, compliance officers, and technical leaders at the largest financial institutions, insurers, and other highly regulated enterprises across EMEA to address their most critical questions about deploying Claude safely and securely — including the security capabilities of our latest generations of Claude models. This is a pre-sales technical role focused on security, compliance, networking, and data architecture. Your job is to walk into a room full of security professionals and demonstrate deep expertise in enterprise security, regulatory compliance, and data protection. Whether you've been a Security Architect, Solutions Architect, Field CTO, or senior pre-sales engineer, what matters is that you understand how large European institutions evaluate and adopt technology, and can speak credibly to their security and compliance concerns. This is a senior role: you will own our most complex and escalated security conversations in the region, often as the decisive technical voice in front of a CISO. We are looking for someone excited to help define how European enterprises should think about security and compliance in the age of AI. How do MCP, autonomous agents, and RBAC work together? How do you deploy frontier models in line with GDPR, EU data residency, and the EU AI Act? If working at the intersection of AI adoption and regulated industries excites you, this is the role for you. Responsibilities: - Serve as the primary security and compliance expert in customer engagements, addressing technical questions about Claude's architecture, data flows, encryption, access controls, and deployment models. - Partner with CISOs, security architects, compliance teams, and DPOs to understand their security requirements and design solutions that meet European regulatory standards (GDPR, EU AI Act, DORA, NIS2, SOC 2, PCI-DSS, and national regulator expectations). - Lead technical deep-dives on network architecture, EU data residency, data retention and Zero Data Retention (ZDR) policies, cross-border data transfers, API security, authentication/authorization, audit logging, and integration patterns for regulated environments. - Support enterprise security reviews, vendor assessments, and due diligence with detailed technical documentation and expert guidance. - Guide customers through EU AI Act readiness, DORA, and NIS2, and position Anthropic within the European competitive landscape. - Collaborate with Sales and Applied AI teams from initial conversations through deployment. - Partner closely with Anthropic’s product and engineering teams to understand Claude's security capabilities, relay customer feedback, and influence the roadmap. - Develop security-focused collateral, reference architectures, and best practices for regulated industries. - Travel regularly across EMEA for security workshops, architecture reviews, and strategic account meetings. You may be a good fit if you have: <ul&gt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Key Responsibilities: - Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development - Independently lead small research projects while collaborating with team members on larger initiatives - Design, run, and analyze scientific experiments to advance our understanding of large language models - Optimize and scale our training infrastructure to improve efficiency and reliability - Develop and improve dev tooling to enhance team productivity - Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications: - Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field - Strong software engineering skills with a proven track record of building complex systems - Expertise in Python and experience with deep learning frameworks (PyTorch preferred) - Familiarity with large-scale machine learning, particularly in the context of language models - Ability to balance research goals with practical engineering constraints - Strong problem-solving skills and a results-oriented mindset - Excellent communication skills and ability to work in a collaborative environment - Care about the societal impacts of your work Preferred Experience: - Work on high-performance, large-scale ML systems - Familiarity with GPUs, Kubernetes, and OS internals - Experience with language modeling using transformer architectures - Knowledge of reinforcement learning techniques - Background in large-scale ETL processes You'll thrive in this role if you: - Have significant software engineering experience - Are results-oriented with a bias towards flexibility and impact - Willingly take on tasks outside your job description to support the team - Enjoy pair programming and collaborative work - Are eager to learn more about machine learning research - Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects - Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research - View research and engineering as

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery. About the role We're seeking an exceptional Research Scientist to join the team. This role combines deep computational biology expertise with frontier AI capabilities, positioning Anthropic at the forefront of AI-driven scientific discovery. As one of the first computational members of this Life Sciences research group, you'll work on a high-impact team that operates at the intersection of computational and experimental biology. You'll bring broad computational biology experience to bear across the team's projects, driving discoveries from large-scale computational analysis of biological data through to results our experimental scientists can test, and moving flexibly between problems as the science demands. You'll have substantial access to Claude and you'll help establish how computational biology operates at Anthropic. This role offers a unique opportunity to shape how AI transforms biological research. You'll work with some of the world's best AI researchers while tackling problems that matter deeply for scientific understanding and biomedicine. If you're excited about using your computational expertise to make fundamental biological discoveries and guide the development of transformative AI systems, we want to hear from you. Key responsibilities - Build, run, and maintain the analysis pipelines that back the team's experimental programs: sequence analysis at petabyte scale, structural bioinformatics, phylogenetic and comparative genomics, design and analysis of high-throughput functional screens, biological sequence modeling, etc. - Partner directly with experimental biologists to design experiments that produce high-quality data, and turn results around fast enough to immediately inform the next experiment - Draw on the literature and curated biological knowledge bases alongside primary data to generate and prioritize hypotheses for experimental follow-up - Stand up and maintain the team's computational infrastructure: data ingestion, workflow orchestration, internal databases, and the interfaces that make all of it accessible to both researchers and AI agents <li class="font-claude-response-body whitespace-normal b

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We're looking for Research Engineers to build the evaluations that tell us — and the world — what Claude can actually do. Your work will turn ambiguous notions of "intelligence" into clear, defensible metrics that researchers, leadership, and the public can rely on. You'll design and implement evaluations across the full spectrum of Claude's capabilities and personality, and build the infrastructure that runs them reliably at scale. You'll partner closely with researchers throughout the lifecycle of a new capability — from defining what to measure, to running the eval against live training checkpoints, to interpreting the results. The goal is to make Anthropic the leader in extremely well-characterized AI systems, with performance that is exhaustively measured and validated across the tasks that matter. Key responsibilities - Design and run new evaluations of Claude's capabilities — reasoning, agentic behavior, knowledge, safety properties — and produce visualizations that make the results legible to researchers and decision-makers - Build and harden the distributed eval execution platform so hundreds of evals run reliably against checkpoints throughout production RL training runs - Own the dashboards researchers and leadership use to monitor model health during training, improving signal-to-noise, reducing latency, and making regressions impossible to miss - Debug anomalous eval results mid-training-run, determine whether the cause is a model change or an infrastructure issue, and communicate the answer clearly under time pressure - Improve the tooling, libraries, and workflows researchers use to implement and iterate on evaluations - Partner with research teams across the full lifecycle of a new capability — from defining what to measure to interpreting results as training progresses - Run experiments to characterize how prompting, sampling, and scaffolding choices affect results on internal and industry benchmarks - Communicate evaluations and their results to internal stakeholders and, where approp

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments: Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences, focusing on raising the floor. About the role: We're looking for an Applied AI Engineer to join our Beneficial Deployments team. You’ll use your deep technical expertise to help partners accelerate their impact through advising on evals, hill-climbing on harnesses, prototyping new agents, etc. You will also work on building ecosystem-level tooling and infrastructure to scale impact beyond individual partnerships. Responsibilities: - Serve as a deep technical partner to mission-driven organizations through advising on evals, agent architectures, context engineering, cost optimization, and more - Provide hands-on support to partner engineering teams through pair programming, prototyping, and code contributions that accelerate their development - Develop public goods infrastructure that benefits entire ecosystems through benchmarks, MCP’s, and Agent Skills - Identify challenges unique to social impact partners, and contribute findings and improvements back to product, engineering, and research - Create technical presentations, demos, and scalable technical content (documentation, tutorials, sample code) to accelerate partner adoption and self-service - Help shape team processes and culture as we scale from 1 to N - Travel occasionally to customer sites for workshops, technical deep dives, and relationship building You might be a good fit if you have: - 4+ years as a Software Engineer, Forward Deployed Engineer, or technical founder - Production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale - Builder credibility that earns trust with technical founders and engineering teams—you've shipped products and can speak from experience - Experience working in ed-tech, healthcare, scientific research, nonprofit, or other mission-driven organizations, understanding their unique challenges and constraints - A love of teaching, mentoring, and helping others succeed - A scrappy mentality - comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £240,000 - £255,000 GBP <div class="content-conclusion"&gt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also. You may be a good fit if you: - Have significant software engineering or machine learning experience, particularly at supercomputing scale - Are results-oriented, with a bias towards flexibility and impact - Pick up slack, even if it goes outside your job description - Enjoy pair programming (we love to pair!) - Want to learn more about machine learning research - Care about the societal impacts of your work Strong candidates may also have experience with: - High performance, large-scale ML systems - GPU/Accelerator programming - ML framework internals - OS internals - Language modeling with transformers Representative projects: - Implement low-latency high-throughput sampling for large language models - Implement GPU kernels to adapt our models to low-precision inference - Write a custom load-balancing algorithm to optimize serving efficiency - Build quantitative models of system performance - Design and implement a fault-tolerant distributed system running with a complex network topology - Debug kernel-level network latency spikes in a containerized environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy:</st

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Apply using this link . Applications for the next cohort of Anthropic Fellows close at 11:59pm PT on July 26 . The cohort is expected to start November 2 . In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the November start date doesn't work for you. This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting . Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect - 4 months of full-time research - Direct mentorship from Anthropic researchers - Access to a shared workspace (in either Berkeley, California or London, UK) - Connection to the broader AI safety and security research community - Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) - Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research progra

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team Our team is organized around the north star goal of building an AI scientist—a system capable of solving the long-term reasoning challenges and basic capabilities necessary to push the scientific frontier. About the Role We're seeking a Science Research Operations team member to build and own the operational infrastructure that keeps our research organization running at full speed. Our science teams are working on some of the hardest and most consequential problems in AI—training large-scale models, running complex experiments, and building novel products at the frontier. What makes that possible isn't just talent: it's the coordination, systems, and programs that let researchers spend their time on the science rather than the overhead around it. This role sits at the intersection of research operations, technical program management, and product strategy. You'll work directly with research scientists and research engineers, doing a mix of tasks including running research partnerships, managing complex internal programs, and helping run the team’s day-to-day operations. You'll also contribute to science product development—helping translate research directions into product strategy and ensuring our production deployment environments reflect our best configurations. This is not a pure coordination role. The best candidates will engage substantively with what the team is building, have a role in determining our strategy, spot problems before they surface, and bring genuine ownership to the systems and programs they run. Responsibilities: - Build and manage custom expert contractor networks, sourcing domain specialists for eval and training data work that requires expertise beyond standard channels - Run research partnerships with external partners, from scoping through delivery - Provide end-to-end TPM support for major research pushes—coordinating across teams, tracking dependencies, and keeping stakeholders aligned - Ensure that our research progress is complemented by products that enable scientists to make maximal use of model capabilities. - Support recruiting efforts. - Coordinate external communications for the team, including supporting blog posts and preparing public-facing materials - Partner with product teams to contribute to science product strategy, product design, and novel product integrations where research and product intersect - Own team logistics including onboarding coordination, team events, and operational programs that improve team efficiency You may be a good fit if you: - Have experience in research operations, technical program management, or a related role in a fast-moving technical environment - Can context-switch fluidly between operational work (logistics, tracking, coordination) and higher-order work (strategy, partnerships, product thinking) - Have a technical background, with experience in software development, machine learning, or biology R&D. - Are comfortable working directly with research scientis

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Recruiting Research Scientist to join our People Data Solutions team. You’ll be the research expert supporting our Recruiting organization, using rigorous scientific methods to advance our understanding of recruiting funnels, interview effectiveness, candidate experience, and recruiting capacity. This role sits at the intersection of organizational science, behavioral research, and people strategy – developing novel frameworks and conducting systematic research that drives evidence-based people decisions across our growing organization. This role offers the opportunity to make a significant impact on both our recruiting practices and the broader field of people science at a leading AI safety company. Responsibilities Research design & scientific inquiry - Design and execute systematic research studies to answer fundamental questions about recruiting funnel health, assessment quality, candidate experience, and quality of hire - Generate and test hypotheses about sourcing strategies, interview design, and selection decisions using rigorous experimental and quasi-experimental methods - Conduct mixed-method research to understand what are the drivers and blockers to recruiting operations. - Navigate research ethics considerations when studying candidate data, ensuring responsible research practices Selection & assessment research - Design and execute validation studies to assess the quality of interviews and other selection tools - Utilize psychometric techniques to analyze and improve interviewer calibration and rating consistency - Lead investigative research into innovative approaches for candidate assessment Metrics design and governance - Design the metrics framework for recruiting org health — defining the canonical KPIs, dimensions, and definitions that leadership uses to understand funnel performance, capacity, and hiring quality - Establish the governance and definitional rigor that keeps metrics consistent across tools and reporting surfaces Analytical solution building - Architect analytical solutions that convert research insights into actionable products, empowering stakeholders to execute data-driven scenario and strategic planning - Quantify the adoption and downstream impact of deployed tools, driving iterative improvements Visualization & communication - Build compelling visualizations and dashboards that make complex research findings accessible to diverse audiences - Present research findings to senior leadership with clear, actionable recommendatio

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's inference fleet serves Claude to millions of users across our own products and the world's largest cloud platforms. The stack that makes this possible is deep and tightly coupled: accelerator kernels, model servers, distributed routing, autoscaling, capacity management. Every layer affects the others, often in ways that are hard to see in isolation. The Inference System Dynamics team is responsible for understanding that whole system and holding it to a high bar across four dimensions: throughput, latency, reliability, and correctness . We measure how the fleet performs against its theoretical performance frontier, run cross-layer investigations to explain the gaps, and own the correctness checks that make sure Claude's outputs are right, not just fast, across hardware platforms and serving configurations. We don't own the individual components. We instrument and model them, find the highest-leverage opportunities across them, and partner with the owning teams to land the wins. You'll work across all four areas. One week that might mean tracing a tail-latency regression from request timing down through routing and batching into a kernel overhead; the next it might mean tightening a correctness eval so it catches an output regression introduced by a quantization change. We're looking for performance engineers who treat correctness as part of performance. Key Responsibilities - Run cross-layer performance investigations across throughput, latency, and reliability, sizing the gap between actual fleet performance and theoretical rooflines, identifying root causes, and quantifying the value of closing them - Own and improve the correctness evaluation pipeline that validates model output quality across hardware platforms, numerics, and serving configurations, and lead the investigation when it catches a regression - Build the observability, dashboards, and modeling tools that make throughput, latency, cost, reliability, correctness, and their interactions legible across the stack - Partner with kernel, serving, routing, autoscaling, and capacity teams to prioritize and land the highest-impact optimizations your analysis surfaces - Ruthlessly stack-rank a large surface area of opportunities by impact and effort, and say no to the ones that don't make the cut Minimum Qualifications - Hands-on performance engineering experience: profiling, roofline analysis, latency/throughput optimization, and root-cause investigation in complex production systems - Proficiency in Python, with the ability to read, instrument, and contribute to large production codebases you didn’t write - Solid data analysis skills (e.g. SQL, pandas, or similar) sufficient to turn raw telemetry into clear findings - Ability to communicate quantitative results clearly in writing to influence priorities on teams you don't manage - Genuine interest in correctness as an engineering discipline: numerics, evaluation design, regression detection Preferred Qualifications - Expe

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: Anthropic's ML Performance and Scaling team trains our production pretrained models, work that directly shapes the company's future and our mission to build safe, beneficial AI systems. As a Research Engineer on this team, you'll ensure our frontier models train reliably, efficiently, and at scale. This is demanding, high-impact work that requires both deep technical expertise and a genuine passion for the craft of large-scale ML systems. This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination. During launches, the team works in tight lockstep, responding to production issues that can't wait for tomorrow. Responsibilities: - Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability - Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure - Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance - Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams - Build and maintain production logging, monitoring dashboards, and evaluation infrastructure - Add new capabilities to the training codebase, such as long context support or novel architectures - Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams - Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned You May Be a Good Fit If You: - Have hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems - Genuinely enjoy both research and engineering work—you'd describe your ideal split as roughly 50/50 rather than heavily weighted toward one or the other - Are excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure - Thrive when working on whatever is most impactful, even if that changes day-to-day based on what the production model needs - Excel at debugging complex, ambiguous problems across multiple layers of the stack - Communicate clearly and collaborate effectively, especially when coordinating across time zones or during high-stress incidents - Are passionate about the work itself and want to refine your craft as a research engineer - Care about the societal impacts of AI and responsible scaling Strong Candidates May Also Have: - Previous experience training LLM’s or working extensively with JAX/TPU, PyTorch, or other ML frameworks at scale - Contributed to open-source LLM frame

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Horizons The Horizons team leads Anthropic's reinforcement learning (RL) research and development, playing a critical role in advancing our AI systems. We've contributed to every Claude release, with significant impact on the autonomy, coding, and reasoning capabilities of Anthropic's models. About the role We're hiring for the Cybersecurity RL team within Horizons. As a Research Engineer, you'll help to safely advance the capabilities of our models in secure coding, vulnerability remediation, and other areas of defensive cybersecurity. This role blends research and engineering, requiring you to both develop novel approaches and realize them in code. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers, engineers, and cybersecurity specialists across and outside Anthropic. The role requires domain expertise in cybersecurity paired with interest or experience in training safe AI models. For example, you might be a white hat hacker who's curious about how LLMs could augment or transform your work, a security engineer interested in how AI could help harden systems at scale, or a detection and response professional wondering how models could enhance defensive workflows. You may be a good fit if you: - Have experience in cybersecurity research. - Have experience with machine learning. - Have strong software engineering skills. - Can balance research exploration with engineering implementation. - Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have: - Professional experience in security engineering, fuzzing, detection and response, or other applied defensive work. - Experience participating in or building CTF competitions and cyber ranges. - Academic research experience in cybersecurity. - Familiarity with RL techniques and environments. - Familiarity with LLM training methodologies. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $300,000 - $405,000 USD <strong&gt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are looking for a Technical CBRN-E Threat Investigator to join our Threat Intelligence team. In this role, you will be responsible for detecting, investigating, and disrupting the misuse of Anthropic's AI systems for Chemical, Biological, Radiological, Nuclear, and Explosives (CBRN-E) threats. We are particularly interested in candidates with deep expertise in either chemical defense or biodefense. You will work at the intersection of AI safety and CBRN security, conducting thorough investigations into potential misuse cases, developing novel detection techniques, and building robust defenses against threat actors who may attempt to leverage our AI technology for developing weapons, synthesizing dangerous compounds, or creating biological harm. Your specialized domain expertise will be critical to protecting against some of the most serious potential misuses of AI systems. Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. Responsibilities - Detect and investigate attempts to misuse Anthropic's AI systems for developing, enhancing, or disseminating CBRN-E weapons, pathogens, toxins, or other threats to harm people, critical infrastructure, or the environment - Conduct technical investigations using SQL, Python, and other tools to analyze large datasets, trace user behavior patterns, and uncover sophisticated CBRN-E threat actors - Develop CBRN-E-specific detection capabilities, including abuse signals, tracking strategies, and detection methodologies tailored to dual-use research concerns - Create actionable intelligence reports on CBRN-E attack vectors, vulnerabilities, and threat actor TTPs leveraging AI systems - Conduct cross-platform threat analysis grounded in real threat actor behavior, open-source research, and publicly reported programs - Collaborate with policy and enforcement teams to make informed decisions about user violations and ensure appropriate mitigation actions - Engage with external stakeholders including government agencies, regulatory bodies, scientific organizations, and biosecurity/chemical security research communities - Inform safety-by-design strategies by forecasting how threat actors may leverage advances in AI technology for CBRN-E purposes You may be a good fit if you - Have deep domain expertise in biosecurity, chemical defense, biological weapons non-proliferation, dual-use research of concern (DURC), synthetic biology, or related CBRN-E threat domains - Have demonstrated proficiency in SQL and Python for data analysis and threat detection - Have experience with threat actor profiling and utilizing threat intelligence frameworks - Have hands-on experience with large language models and understanding of how AI technology could be misused for CBRN-E threats - Have excellent stakeholder management skills and ability to work with diverse teams including researchers,

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking a strategic Go-To-Market Recruiter specializing in Applied AI to join our GTM recruiting organization. In this role, you'll focus specifically on building and scaling our Applied AI team - the Pre-Sales architects and technical advisors who help large enterprises successfully integrate and deploy Claude. Working within our broader GTM recruiting team, you'll drive full-cycle recruiting for these critical customer-facing technical roles that bridge our cutting-edge AI technology with real-world business applications. This specialized role requires deep technical recruiting expertise combined with a strong understanding of enterprise SaaS and AI landscapes. You'll collaborate closely with GTM recruiting colleagues while developing targeted strategies for the unique talent needs of our Applied AI organization. You'll help shape how enterprises work with AI systems by building teams that directly influence the safe and beneficial deployment of Claude across industries. Key responsibilities - Lead end-to-end recruiting for Applied AI team roles, including Solutions Architects, Pre-Sales Engineers, front-line managers and other customer-facing technical positions - Partner with Applied AI leadership and GTM recruiting colleagues to develop comprehensive hiring strategies that align with overall GTM objectives - Execute sophisticated sourcing strategies to identify candidates with rare combinations of technical depth, customer empathy, and business acumen - Create exceptional candidate experiences that showcase Anthropic's mission and the unique opportunity to shape enterprise AI adoption - Build pipelines of talent with expertise in LLMs, cloud architecture, enterprise software integration, and technical consulting - Collaborate with GTM recruiting team members to share best practices, market insights, and cross-functional candidate leads - Leverage Claude and other AI tools to enhance recruiting efficiency while maintaining high-touch, personalized engagement - Provide data-driven insights on compensation trends and talent availability specific to the Applied AI market Minimum qualifications - Excel at recruiting for customer-facing technical roles that require both deep technical knowledge and exceptional communication skills - Understand the technical requirements of roles working with LLMs, APIs, cloud architectures, and enterprise system integration - Thrive in collaborative environments, working seamlessly with GTM recruiting colleagues while managing specialized searches - Can effectively assess candidates' abilities to translate complex technical concepts for diverse stakeholders - Have a track record of building trusted advisor relationships with technical hiring managers - Are passionate about using AI to transform recruiting practices while

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team The Universes team within Research is responsible for training AI models to perform complex, difficult, long-horizon agentic tasks in ultra-realistic settings. We design and implement novel training environments that go far beyond what models can do today — environments where models learn to navigate ambiguity, handle interruptions, maintain context over extended interactions, and exercise judgment in open-ended scenarios. About the Role We're looking for Research Engineers to help us build the next generation of training environments for capable and safe agentic AI. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to research direction. You'll work on fundamental research in reinforcement learning, designing training environments and methodologies that push the state of the art, and building evaluations that measure genuine capability. Responsibilities: - Build the next generation of agentic environments - Build rigorous evaluations that measure real capability - Collaborate across research and infrastructure teams to ship environments into production training - Debug and iterate rapidly across research and production ML stacks - Contribute to research culture through technical discussions and collaborative problem-solving You may be a good fit if you: - Are highly impact-driven — you care about outcomes, not activity - Operate with high agency - Have good research taste or senior technical experience, demonstrating good judgment in identifying what actually matters in complex problem spaces - Can balance research exploration with engineering implementation - Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems - Are comfortable with uncertainty and adapt quickly as the landscape shifts - Have strong software engineering skills and can build robust infrastructure - Enjoy pair programming (we love to pair!) Strong candidates may also have one or more of the following: - Have industry experience with large language model training, fine-tuning or evaluation - Have industry experience building RL environments, simulation systems, or large-scale ML infrastructure - Senior experience in a relevant technical field even if transitioning domains - Deep expertise in sandboxing, containerization, VM infrastructure, or distributed systems - &

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand. As Technical Recruiter, Infrastructure, you'll join the small team of recruiters who hire for that organization, owning full lifecycle recruiting for your searches and partnering with infrastructure leaders to turn ambiguous needs into clear search strategies. Key responsibilities - Own full lifecycle recruiting for a portfolio of roles across the Infrastructure organization, from intake through offer and close - Run structured intakes with infrastructure hiring managers, translating ambiguous needs into scoped requirements, calibrated bars, and search strategies - Build and maintain pipelines of specialized infrastructure talent, with an emphasis on passive candidates - Refine infrastructure interview loops, take-home assignments, and scorecards alongside hiring managers, your recruiting counterparts, and Recruiting Operations - Develop deep domain knowledge aligned with the teams you support, so you can identify niche talent with the right specific domain fit - Advise hiring managers with market data and candid calibration feedback, and influence decisions through credibility rather than volume - Partner with Compensation, People Partners, and Mobility to structure equitable offers and guide candidates to close - Handle sensitive role and candidate information with discretion, including for searches whose scope is confidential Minimum qualifications - Deep full lifecycle recruiting experience, with substantial time supporting infrastructure, platform, or comparably technical engineering organizations - Ability to hold a substantive technical conversation about infrastructure domains such as Kubernetes and container orchestration, cloud networking, cluster networking, and systems languages, and to evaluate technical qualifications rather than match keywords - Proficiency with an applicant tracking system like Greenhouse and other modern sourcing tools - Experience partnering directly with hiring managers on intake, bar calibration, and interview loop design - Sound independent judgment on candidate quality, and the ability to independently partner with multiple hiring managers on complex searches - A strong sense of ownership over your work, and the adaptability to adjust as priorities and hiring needs shift - Genuine interest in Anthropic's mission and in the role a strong infrastructure function plays in achieving it <h2&gt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Safeguards team is seeking a Red Team Engineer to help ensure the safety of our deployed AI systems and products. In this role, you'll take an adversarial approach to uncover vulnerabilities across our product ecosystem before they can be exploited by malicious actors. Your work will span from technical infrastructure vulnerabilities on our products to emergent risks from advanced AI capabilities. While you'll bring best practices from traditional security approaches, the focus is on broader safety implications and novel abuse unique to advanced AI systems and associated products. You'll investigate the full spectrum of potential abuse — from coordinated account manipulation and payment fraud to novel exploitation of product features — and simulate sophisticated threat actors who chain multiple attack vectors to achieve their objectives. Key responsibilities - Conduct comprehensive adversarial testing across Anthropic's product surfaces, developing creative attack scenarios that combine multiple exploitation techniques - Research and implement novel testing approaches for emerging capabilities, including agent systems, tool use, and new interaction paradigms - Design and execute "full kill chain" attacks that emulate real-world threat actors attempting to achieve specific malicious objectives - Build and maintain systematic testing methodologies that evaluate every aspect of our systems - Develop automated testing frameworks to enable continuous assessment at scale - Collaborate with Product, Engineering, and Policy teams to translate findings into concrete improvements - Help establish metrics for measuring detection effectiveness of novel abuse Minimum qualifications - Experience in penetration testing, red teaming, or application security - Experience in model jailbreaking and testing large-scale agentic workflows for non-obvious prompt injection vectors - Strong technical skills in web application security, including hands-on expertise with security testing tools (e.g., Burp Suite, Metasploit, custom scripting frameworks) - Experience building custom automation, including LLM-specific testing frameworks - A track record of discovering novel attack vectors and chaining vulnerabilities in creative ways - A public body of work such as CVEs, blog posts, or disclosed bug bounty reports - Strong written and verbal communication skills, with the ability to explain technical concepts to varied audiences Preferred qualifications - Experience with AI/ML security or adversarial machine learning - Understanding of AI safety considerations beyond traditional security, including modern guardrails against jailbreaks - Experience testing API security and rate-limiting systems - Background in testing business logic vulnerabilities and authorization bypass techniques - Background in anti-fraud, trust & safety, or abuse prevention syste

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Third Party Risk Management (TPRM) team sits within Security GRC and is responsible for risk management of our vendor and partner relationships, making risk visible to the people who need to act on it, and driving it down. We're building the program for what a frontier AI lab actually has at stake: the models, the research IP, the safety commitments, and the infrastructure that keeps Claude available to customers. The program is designed agent-first, with an AI risk agent handling intake, tiering, and evidence collection so that people spend their time on judgment, remediation, and the vendors that matter most. This role owns the top of that risk stack. You will run the Mission Critical and Highest-Risk vendor portfolios. On the Mission Critical side that means the compute, data center, and data-pipeline vendors where a tier rating is the start of the conversation rather than the end of it: exit and failover planning, single-point-of-failure analysis and treatment, and financial and solvency screening. On the Highest-Risk side that means the vendors with the deepest access to our data and systems, where you'll make sure assessment depth matches the exposure and drive remediation on what those assessments surface. You'll also carry the operational baseline the whole team shares (intake reviews, QA on agent output, escalations, reporting) so the program keeps moving while the portfolio work is underway. Key responsibilities - Own the Mission Critical vendor portfolio: maintain the tiered list, validate it against business impact analysis findings, support exit and failover planning, and drive risk treatment for single points of failure with Procurement, Business Continuity, and business owners - Manage the Highest-Risk vendor portfolio: keep security, privacy, and compliance assessment depth aligned to active vendor exposure, and drive remediation with the relevant domain teams - Support vendor incident response: vendor-side impact assessment, business-owner coordination, and post-incident risk treatment - Run inherent risk assessments through the intake workflow: review agent-prefilled tiering, evaluate vendor controls and evidence across security, privacy, compliance, and operational risk, determine residual risk, and route to domain reviewers where deeper assessment is warranted - Operate the TPRM issue management workflow: document findings with clear risk statements, assign owners, track treatment to closure - Tune and maintain the TPRM Risk Agent alongside the team through prompt development, backtest calibration, error analysis, and output QA - Contribute to KPI/KRI reporting on portfolio coverage and cycle time Minimum qualifications - Experience running third party or vendor risk assessments end to end at a technology company: scoping the engagement, determining inherent risk, reviewing controls and evidence, documenting residual risk, and driving findings to closure - Working knowledge of risk fundamentals (inherent and residual risk, control effectiveness, compensating controls, risk acceptance) and the judgment to apply them when the evidence is incomplete or the answer isn

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is hiring Technical Architects: hands-on builders and live technical communicators who help our customers go from "we bought Claude" to "our people use it every day." You'll be the technical partner our CSMs pull into the room whenever the work gets technical. For our customers, that's most of the time. One week you're running an advanced Claude Code hackathon for 1000 engineers at a global bank. The next you're on a call with their CISO walking through data handling, SSO, and governance controls. The week after, you're pair-building a plugin with a customer's platform team and debugging a SCIM sync live while thirty people watch. You are the helper people look for. This is a post-sale role. You'll work alongside CSMs, Applied AI, Support, FDEs, and more. We're looking for technologists who could have been researchers or staff engineers, but who get the most energy from helping customers get unstuck by teaching them something new. What you'll do - Be the technical lead in customer-facing moments across the post-sale journey: onboarding workshops, developer hackathons, live troubleshooting, executive security reviews, adoption working sessions. - Build and ship working software (Claude Code plugins, agents, sub-agents, MCP integrations, Cowork skills) both as customer deliverables and as reusable field assets. - Drive adoption of the Claude Code capabilities that make the product stick (sub-agents, skills, hooks, MCP, headless mode, managed settings) and turn new capabilities into field-ready demos and guides within days of release. - Own enterprise deployment and identity conversations: SSO (SAML/OIDC), SCIM provisioning, role, seat, and spend-limit management, sandbox and permission design. Sit credibly across from CISOs and security architects. - Advise and unblock customers running production workloads on the Anthropic API and on Bedrock / Vertex, in close partnership with Applied AI. - Teach. Design and deliver enablement that turns users into daily active developers, for audiences ranging from senior staff engineers to business users new to AI and develop the customer champions who carry adoption after you leave the room. - Represent Anthropic at customer all-hands and builder events, and bring structured field signal back to the Claude Code and Cowork product teams. - Partner tightly with CSMs as their technical counterpart, and with Applied AI, security specialists, Product Support, Engineering, and Sales as the connective technical tissue of the account. What we're looking for - You build. You've shipped real software, you've used Claude Code or comparable AI coding tools yourself, and you can stand behind your engineering choices. - You hold the room. You're at ease being the technical voice in front of senior developers, IT and security leaders, and non-technical stakeholders (often in the same hour), and you stay calm and useful when something breaks live. - You like the messy middle. You’re comfortable being pulled into an ambiguous customer situation and developing a solution in real time.</li&g

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As an Applied AI team member at Anthropic, you will be a pre-sales architect focused on becoming a trusted technical advisor to the UK and Northern Europe public sector, with a primary focus on UK Central Government departments, executive agencies, and arm's length bodies, and a reach extending across devolved administrations, local government, the NHS, and Northern European public sector markets. This includes a growing focus on defence and national security, working with the MOD and intelligence agencies on some of the UK's most sensitive and mission-critical challenges. You will help these organisations understand the value of Claude and paint the vision for how they can successfully integrate and deploy Claude into their technology estates to modernise operations, improve policy delivery, and transform citizen services. You’ll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex mission challenges while maintaining our high standards for safety and reliability. Working closely with our Sales, Product, Engineering, and Partnerships teams, you’ll guide customers from initial technical discovery through successful deployment. You’ll leverage your expertise to help customers understand Claude’s capabilities, develop evals, and design scalable, compliant architectures that maximise the value of our AI systems within the constraints that public sector organisations operate under. Responsibilities - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between departmental outcomes, policy objectives, and technical implementation. - Serve as the primary technical advisor to public sector customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams and stakeholders to drive customer success. - Support customers building with Claude Code, the Claude API, and Claude for Enterprise. - Create and deliver compelling technical content tailored to different audiences. You will need to span the gamut from technical deep dives for engineering and delivery teams up to business-value conversations with senior civil servants and C-suite executives (Permanent Secretaries, Directors General, SROs, CDIOs). - Support defence and national security engagements, including with the MOD and intelligence agencies, designing solutions that work within the security, classification, and accreditation constraints of these environments. - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack, with alignment to NCSC guidelines, Cyber Essentials Plus, the Government Security Classifications framework, the Technology Code of Practice, and the Service Standard. - Help customers develop evaluation frameworks to measure Claude’s performance for their specific use cases. - Identify common integration patterns across the UK publi

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pretraining team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. Key Responsibilities: - Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development - Independently lead small research projects while collaborating with team members on larger initiatives - Design, run, and analyze scientific experiments to advance our understanding of large language models - Optimize and scale our training infrastructure to improve efficiency and reliability - Develop and improve dev tooling to enhance team productivity - Contribute to the entire stack, from low-level optimizations to high-level model design Qualifications: - Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field - Strong software engineering skills with a proven track record of building complex systems - Expertise in Python and experience with deep learning frameworks (PyTorch preferred) - Familiarity with large-scale machine learning, particularly in the context of language models - Ability to balance research goals with practical engineering constraints - Strong problem-solving skills and a results-oriented mindset - Excellent communication skills and ability to work in a collaborative environment - Care about the societal impacts of your work Preferred Experience: - Work on high-performance, large-scale ML systems - Familiarity with GPUs, Kubernetes, and OS internals - Experience with language modeling using transformer architectures - Knowledge of reinforcement learning techniques - Background in large-scale ETL processes You'll thrive in this role if you: - Have significant software engineering experience - Are results-oriented with a bias towards flexibility and impact - Willingly take on tasks outside your job description to support the team - Enjoy pair programming and collaborative work &l

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Sales Manager at Anthropic, you’ll lead a team of Strategic Account Executives driving the adoption of safe, frontier AI by securing strategic deals with top enterprises in the Telco, Media, and Retail verticals. You’ll leverage your leadership and consultative sales expertise to propel revenue growth while developing a high-performing team of AEs. Working closely with Applied AI Engineering and Product teams, you’ll help customers embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM and Marketing teams, you’ll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. The ideal candidate will have a passion for developing people, identifying market opportunities, and executing strategies to capture them. By leading the deployment of Anthropic’s emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI. Key responsibilities: - Recruit, coach, and retain Strategic Account Executives with deep industry and platform-selling expertise; develop leadership talent and create career paths that keep top performers growing - Codify the use cases, proof points, reference stories, and sales motions that make wins repeatable within each industry, partnering with Marketing, Enablement, and partner teams to scale them - Engage personally with C-level executives on priority pursuits, building business cases and value narratives and navigating complex procurement, security, and legal processes through to production deployment and expansion - Own the organization's revenue targets and operating rhythm, instilling pipeline-generation discipline and running forecasting, deal inspection, and account planning cadences that make performance predictable and coachable across a high-volume book of business - Partner closely with Applied AI, Solutions Architecture, and Product to design solutions, prove value quickly, and translate industry needs into product and roadmap input - Orchestrate cross-functional and partner motions with Customer Success, Marketing, Partnerships, Legal, and cloud partners to deliver a seamless customer experience, and represent Anthropic with customers and at industry events as a visible, trusted leader Minimum qualifications: - Experience leading strategic sales teams that sell technical, complex products such as API-first platforms, cloud infrastructure, or data and machine learning platforms - A track record of winning and growing enterprise customers, including building C-suite relationships, in one or more of our focus industries (telecommunications, media & entertainment, retail & consumer, industrials & manufacturing, or business services) - Experience designing go-to-market coverage for a strategic sales team, including but not limited to account prioritization - Operational rigor across both a high-volume pipeline and complex, multi-stakeholder sales cycles, balancing velocity with deal quality and forecasting accurately in fast-changing environments - Credibili

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery. About the role We are hiring Research Associates: early-career bench scientists who will join a small team to help establish our biology research program. This is an entry-level role, great for individuals who have done some research during an undergrad or masters program and may be considering pursuing a PhD in Life Sciences in the future. You'll work directly alongside senior scientists, executing and troubleshooting experiments at the bench while learning advanced techniques in a fast-moving, highly collaborative environment. We value curiosity, careful hands, and the willingness to take ownership of a result. Our scientists are eager to teach; we're hiring for motivation and trajectory as much as for existing skill. This is a fully hands-on bench role — while familiarity with computational biology and bioinformatics is welcome, the role does not involve AI/ML model development. Key responsibilities - Execute molecular biology and biochemistry experiments at the bench under the direction of senior scientists - Maintain meticulous, reproducible records and contribute to shared protocols - Troubleshoot experiments, propose adjustments, and present results clearly in group meetings - Maintain mammalian and bacterial cell lines, materials stocks, and reagent inventories - Learn and adopt new techniques rapidly as projects evolve, with training provided Minimum qualifications - Have hands-on research experience in molecular biology, biochemistry, or a closely related field - Are proficient with foundational molecular biology techniques: PCR, gel electrophoresis, molecular cloning, and plasmid preparation &l

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Training and serving frontier AI models requires compute infrastructure at a scale and density that pushes past what conventional data center designs were built to handle. Anthropic’s Data Center team is responsible for delivering that physical infrastructure — partnering with build partners, equipment manufacturers, and vendors to stand up facilities that can reliably cool some of the largest accelerator clusters in the industry. As a Senior Data Center Mechanical Engineer based in Sydney, you’ll lead the design direction and technical oversight of building mechanical systems — cooling, chilled-water distribution, liquid cooling, plumbing, and fire protection — across our rapidly expanding Asia Pacific (APAC) portfolio. This is a senior individual contributor role focused on driving and reviewing mechanical design from concept through detailed design and construction documentation produced by external engineering firms and development partners, ensuring every facility meets Anthropic’s standards for reliability, efficiency, and scalability. You’ll own the mechanical design direction from Basis of Design through construction and commissioning, serving as the primary technical interface between Anthropic’s internal teams and our external engineering and development partners. A central part of this role is speed-to-capacity through prefabrication and modular construction — modular cooling skids, prefabricated piping assemblies, and design for offsite manufacture that compress schedules and reduce onsite labor. You’ll bring deep familiarity with Australian mechanical, hydraulic, and fire codes and the local regulatory environment, and ensure the cooling architecture keeps pace with rapidly increasing rack densities and the shift toward direct-to-chip liquid cooling. Strong candidates will bring deep mission-critical mechanical design experience and the judgment to make sound trade-offs when the standard playbook doesn’t apply. Responsibilities Design direction & review - Drive mechanical design concepts for data center cooling plants, chilled-water distribution, liquid cooling (direct-to-chip and CDUs), plumbing, and fire protection systems. - Review and direct design drawings, specifications, and construction documentation produced by external engineering firms, ensuring alignment with Anthropic’s Basis of Design and owner requirements. - Evaluate design submittals, shop drawings, and equipment selections; respond to RFIs with clear technical direction. - Identify design conflicts and drive resolution across mechanical, electrical, and controls disciplines. - Maintain and evolve Anthropic’s internal mechanical design standards and reference configurations. Prefabrication & modular delivery - Drive Anthropic’s prefabricated and modular mechanical strategy — modular cooling skids, prefabricated piping and pump assemblies, and design for offsite manufacture and onsite assembly — to accelerate deployment a

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's researchers generate and depend on enormous amounts of data — training runs, evaluations, RL transcripts, annotations etc... The Research Data Platform team builds the systems that make that data easy to produce, find, query, and trust. We work in two modes: we build platform components that other systems plug into (for example, a metrics library that training frameworks integrate to record and retrieve run data), and we own core datasets end to end (for example, the data pipeline behind RL transcripts). As the team's tech lead, your job starts with our users. You'll work directly with researchers — and with the engineers who support them — to understand how they actually work, where managing data slows them down, and where a well-built platform component or a well-curated dataset would change what's possible. You'll turn what you learn into technical direction for the team, in partnership with the team's manager, who owns priorities and people. A central ambition you'll drive: a small set of canonical, well-documented datasets — starting with the core data model for RL — that researchers trust and standardize on, rather than every team managing its own copies. You'll spend your first few months close to the code and close to users: shipping improvements in our core systems, embedding with research teams, and building your own map of their workflows. As the team grows, this role has a natural path into formal people leadership for someone who wants it. Responsibilities - Work directly with researchers and the engineers supporting them to understand their workflows, identify the highest-leverage opportunities, and shape what the team builds next - Set the technical direction for the team across our platform and our datasets - Design and build platform components that other teams plug into — libraries, services, and interfaces such as the metrics library used by training frameworks - Own core datasets end to end: the pipelines that produce them, the schemas that define them, and the documentation and guarantees that make researchers trust them - Drive convergence toward canonical datasets — including the core data model for RL transcripts — that research teams standardize on - Lead complex, multi-quarter projects that span several systems and teams, staying hands-on in the code - Raise the team's technical bar through design reviews, mentorship, and the quality of your own work You may be a good fit if you: - Have built and operated data-intensive systems at scale — pipelines, storage layers, query systems — with strong instincts for data modeling and schema design that hold up as usage grows - Have set technical direction for a team, or owned the architecture of a data platform that other teams build on - Treat internal users as customers: you do the discovery work, iterate with users, and measure success by adoption rather than by shipping - Understand that researchers aren’t typical internal customers — the work is exploratory by nature, workflows differ from team to team, and requirements are discovered through experiments rather than specified up f

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We believe that learning is fundamental to human agency. Education Labs studies how people learn and build capability with AI, and we close the loop between what we discover and learning tools the world can access. As our first dedicated education researcher, you will strengthen how the team measures learning and AI fluency so our experiments produce trustworthy evidence. You will design the instruments, build the tools, run the studies, and translate findings into changes across our product experiments and action research in real learning settings. You operate at the frontier where the right measures often do not exist yet and have to be built. This is a hands-on research role embedded in a small team. You will publish and influence thinking across Anthropic, and you will also help decide what is working well enough to scale, what should be handed off to another team, and what should be spun down. We care about learning experiences that make people progressively more capable, curious, and empowered over time. Responsibilities - Design and run mixed-methods studies on how people develop real skill with AI, measuring success by capability growth rather than engagement. - Build and validate the instruments, measures, and evaluation methods the team relies on, so that findings hold up to scrutiny and can be trusted by research, product and policy partners. - Translate research insights into shipped product, curriculum, and model-level improvements through close collaboration with engineers, designers, and researchers. - Generate net-new insights about how AI is reshaping learning, and how communities and organizations can organize to learn alongside it. - Communicate your work through clear writing, prototypes, and presentations that shape thinking across the organization. - Create tools using code and software to collect validated metrics at scale. You may be a good fit if you have - A research background in learning sciences, education, cognitive science, HCI, educational psychology, or a closely related field, whether formal or self-directed. - Strong mixed-methods skills: experimental design, measurement and psychometrics, qualitative methods, and the judgment to choose the right approach for the question. - Hands-on technical skill in Python, data analysis, and working with LLMs, enough to run your own analyses and prototype new measures. - Comfort deriving insight from imperfect, dynamically changing data, and comfort making research decisions with incomplete information while holding a high bar. - Comfort with ambiguity and undefined problem spaces, plus a bias toward rapid, iterative inquiry and quick learning loops. - Clear communication and a track record of cross-functional collaboration with product, design, engineering, and research partners. <li

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Team The Frontier Red Team (FRT) is a small, focused technical research team within Anthropic's Policy organization. Our goal is to make the entire world safer in an era of advanced AI by understanding what these systems can do and building the defenses that matter. In 2026, we're focused on researching and ensuring safety with self-improving, highly autonomous AI systems, especially ones related to cyberphysical capabilities. See our previous related work on exploits , partnering with Mozilla , and zero days . This is early-stage, high-conviction research with the potential for outsized impact — Glasswing is one example. Note: We are exclusively hiring in SF. We support relocation, but all hires must relocate before starting. About the Role In the last year, we've seen compelling signs that LLMs and agents are increasingly capable of novel cyber capabilities. We think 2026 will be the year where models reach expert-level, even superhuman, in several cybersecurity domains. This is a novel and massive threat surface. As a Research Scientist on FRT focusing on cyber, you'll build the tools and frameworks needed to defend the world against advanced AI-enabled cyber threats. Senior candidates will have the opportunity to shape and grow Anthropic's cyberdefense research program, working with Security, Safeguards, Policy, and other partner teams. This work sits at the intersection of AI capabilities research, cybersecurity, and policy—what we learn directly shapes how Anthropic and the world prepare for AI-enabled cyber threats. This is applied research with real-world stakes. Your work will inform decisions at the highest levels of the company, contribute to demonstrations that shape policy discourse, and build the technical defenses that we will need for a future of increasingly powerful AI systems. What You'll Do - Develop systems, tools, and frameworks for AI-empowered cybersecurity, such as autonomous vulnerability discovery and remediation, malware detection and management, network hardening, and pentesting - Design and run experiments to elicit and evaluate autonomous AI cyber capabilities in realistic scenarios - Design and build infrastructure for evaluating and enabling AI systems to operate in security environments - Translate technical findings into compelling demonstrations and artifacts that inform policymakers and the public - Collaborate with external experts in cybersecurity, national security, and AI safety to scope and validate research directions - Senior candidates will also set research strategy, define what problems are worth solving, own the technical roadmap, and manage relationships with cross-functional partners Sample Projects - Building frameworks and tools that enable AI models to autonomo

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a leader within our Enterprise Industries sales team, you will build and lead an industry-aligned team that brings transformational AI to enterprises across telecommunications, media & entertainment, retail & consumer, industrials & manufacturing, and business services. These are companies rethinking how they serve customers, create and distribute content, run stores and supply chains, and operate physical infrastructure — and they're looking for a partner they trust to take frontier AI from promising pilots into production at the core of their business. You'll own a broad portfolio of enterprise accounts at very different stages of AI adoption, from organizations already running Claude in production to those just beginning their journey. You will lead Enterprise Account Executives, design the coverage and territory model, and build the repeatable, industry-specific plays that turn early wins into durable, scaled adoption. The selling is technical and multi-stakeholder — platform decisions, security and procurement rigor, and solutions built on Claude through our API, Claude for Enterprise, Claude Code, and partner cloud platforms — and you'll shape strategy and operating rhythm while staying personally engaged with executives on the pursuits that matter most. This is a rare opportunity to build a team, not just run a number: to shape how a broad cross-section of the economy adopts frontier AI, and to do it at a company where safety, trust, and long-term customer outcomes are central to how we sell. Key responsibilities: - Recruit, coach, and retain Enterprise Account Executives with deep industry and platform-selling expertise; develop and retain top talent - Codify the use cases, proof points, reference stories, and sales motions that make wins repeatable within each industry, partnering with Marketing, Enablement, and partner teams to scale them - Engage personally with C-level executives on priority pursuits, building business cases and value narratives and navigating complex procurement, security, and legal processes through to production deployment and expansion - Own the team’s revenue targets and operating rhythm, instilling pipeline-generation discipline and running forecasting, deal inspection, and account planning cadences that make performance predictable and coachable across a high-volume book of business - Partner closely with Applied AI, Solutions Architecture, and Product to design solutions, prove value quickly, and translate industry needs into product and roadmap input - Orchestrate cross-functional and partner motions with Customer Success, Marketing, Partnerships, Legal, and cloud partners to deliver a seamless customer experience, and represent Anthropic with customers and at industry events as a visible, trusted leader Minimum qualifications: - Experience leading enterprise sales teams that sell technical, complex products such as API-first platforms, cloud infrastructure, or data and machine learning platforms - Player-coach sales leader who has personally built and run a high-velocity greenfield motion, someone who thinks in coverage models, PG cadence, and repeatable plays first, deals second

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: We are looking for Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints. This is no longer true in a world of LLMs! Your job will be to design new architectures for how information is organized, and train language models to optimally use those architectures. Responsibilities: - Designing and implementing from scratch new information architecture strategies - Performing finetuning and reinforcement learning to teach language models how to interact with new information architectures - Building “hard” knowledge base eval sets to help identify failure modes of how language models work with external data - Designing and evaluating advanced agentic search capabilities. You may be a good fit if you: - Are a very experienced Python programmer who can quickly produce reliable, high quality code that your teammates love using - Have good machine learning research experience - Have experience developing software that utilizes Large Language Models such as Claude - Are results-oriented, with a bias towards flexibility and impact - Pick up slack, even if it goes outside your job description - Enjoy pair programming (we love to pair!) - Want to partner with world-class ML researchers to develop new LLM capabilities - Care about the societal impacts of your work - Have clear written and verbal communication Strong candidates will also have experience with: - Collaborating with product teams to quickly prototype and deliver innovative solutions - Building complex agentic systems that utilize LLMs - Developing scalable distributed information retrieval systems, such as search engines, knowledge graphs, RAG, indexing, ranking, query understanding, and distributed data processing The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of expe

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic's research organization works across the full model development lifecycle, from pre-training and post-training to alignment, interpretability, and safety, each operating at the frontier of AI development. As a Technical Program Manager for Research, you'll define and build the programs that research teams need most. You'll move across research areas like compute, evals, RL environments, and emerging research initiatives, going deep enough in each to understand how researchers work and what they need. You'll identify where the biggest opportunities for impact lie, find the highest-leverage gaps, and build the programs, processes, and tooling that allow researchers to focus on research. This is a 0-to-1 role: you'll explore new domains as priorities shift, determine what each one needs, and create lasting impact where none existed before. Note: This role may require responding to incidents on short-notice, including on weekends. Responsibilities - Embed deeply within a research domain to understand the technical landscape, build trust with researchers and technical leaders, and identify the highest-leverage problems to solve, knowing the surface area will shift over time as research priorities evolve - Move fluidly across research areas like compute, evals, RL environments, and emerging research initiatives, picking up new domains quickly and getting to depth fast - Drive end-to-end execution of complex, ambiguous research initiatives spanning multiple teams, often without established playbooks or precedent - Establish processes and frameworks that bring structure to unstructured research environments without slowing researchers down - Lead efforts like large-scale compute resource planning, including allocation, efficiency, and prioritization across research and production workstreams - Drive eval readiness for model launches by standardizing results, shaping eval plans early, improving tooling, and ensuring honest, transparent reporting across research, product, and marketing - Own execution and operational health of RL environments across major training runs, coordinating cross-team trade-offs and feeding insights back into roadmap planning - Equip research leadership to make decisions quickly by going deep on technical tradeoffs and presenting clear, actionable recommendations - Act as the connective tissue between research, engineering, and product teams to reduce chaos and accelerate execution You May Be a Good Fit If You - Have a background in ML research or engineering with several years of experience building technical programs from scratch, ideally with hands-on exposure to training, evaluation, or large-scale distributed systems - Are a fast learner who can ramp on unfamiliar technical domains quickly and contribute meaningfully to discussions with researchers - Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in fast-moving research environments - Have a track record of operational ownership of c

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic is looking for an Engineering Manager to lead the Agent Prompts & Evals team. This team owns the infrastructure that lets Anthropic ship model and prompt changes with confidence — the eval frameworks, system prompt pipelines, and regression-detection systems that every model launch depends on. When a new Claude model is ready to ship, this team is the one answering “is it actually better in our products?” When a product team wants to change how Claude behaves, this team owns the tooling that tells them whether they broke something. It’s a platform team whose platform is model behavior itself. The team sits deliberately at the seam between product engineering and research. You’ll partner closely with other evals groups across the company on shared infrastructure and methodology, with product teams who are shipping features on top of Claude, and with the TPMs and research PMs driving model launches. The pace is set by the model release cadence, and the team operates as both a platform owner and a hands-on partner during launch periods. You don’t need a research background, but you do need to want to learn how to measure things like “is Claude being too sycophantic” or “did web search get worse.” The best version of this role is someone who’s built strong platform or devtools teams before and is excited to apply that skillset to a domain where the thing you’re measuring is a language model. Responsibilities - Lead and grow a team of prompt engineers and platform software engineers - Own the product-side eval platform: the frameworks, dashboards, bulk runners, and CI integrations that product teams use to measure Claude’s behavior and catch regressions before they ship - Own system prompt infrastructure: versioning, deployment, rollback, and review tooling for the prompts that run in production across claude.ai , the API, and agentic surfaces - Be a steady hand through model launches — these are the team’s highest-stakes operational moments and the EM is the backstop when things get chaotic - Build durable collaboration with other evals groups across the company; this means real work on ownership boundaries, shared roadmaps, and avoiding tragedy-of-the-commons on shared eval infrastructure - Recruit, close, and retain engineers who want to work at the intersection of product engineering and model behavior - Shape where the team invests next: there are credible paths into frontier eval development, model launch automation, and deeper prompt engineering support, and part of the job is sequencing them - Push the team toward measuring things that are hard to measure — behavioral drift, prompt quality, harness parity — not just things that are easy You May Be a

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Domain Scaling team has the goal to make Claude world-class at real-world knowledge work in domains like finance, healthcare, and legal. This is a unique role that combines executing directly on applied research and data sourcing (real-world and synthetic) to improve our models. You'll own the end-to-end process of creating RL environments for new capabilities: identifying high-value tasks, designing reward signals, managing vendor relationships, and measuring impact on model performance. Responsibilities - Own the data strategy for knowledge work verticals end-to-end, from task sourcing through RL training - Manage technical relationships with external data vendors, including evaluation of data quality and reward design - Collaborate with domain experts to design data pipelines and evaluations - Explore novel ways of creating RL envs for high value tasks - Develop and improve QA frameworks to catch reward hacking and ensure env quality - Run generalization experiments to measure how data strategy changes improve model capabilities - Partner with other RL research teams and product teams to translate capability goals into training envs and evals You may be a good fit if you - Have experience with fine-tuning large language models for specific domains or real-world use cases - Have experience with reinforcement learning, reward design, or training data curation for LLMs - Are comfortable managing technical vendor relationships and iterating quickly on feedback - Find value in reading through datasets to understand them and spot issues - Have strong cross-functional collaboration skills - Are passionate about making AI more useful and accessible across different industries - Are excited about a role that includes a combination of applied research and hands-on data work Strong candidates may also - Have experience training production ML systems - Have experience designing evals or benchmarks for LLMs - Have domain expertise in a vertical where we would like to make our models more useful - Have experience working with external vendors or technical partners The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: <div class

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities - Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review - Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis - Work closely with product and design teams to scope, prototype, and ship features for life sciences users - Partner with external biotech, pharma, and academic users to understand their workflows and turn feedback into product improvements - Build and maintain the engineering infrastructure behind our biology product surface — tool scaffolding, data pipelines, eval harnesses - Translate biological domain knowledge into product requirements and evaluation criteria that guide model improvement Minimum Qualifications - Experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar - Experience working in drug discovery or development at a biotech or pharma company, or conducted fundamental research in an academic setting — with an understanding of what real scientific workflows look like and where they break down - Strong software engineering skills: comfortable building production-quality Python, working in large codebases, and owning infrastructure end-to-end - Hands-on experience training or fine-tuning ML models (LLMs, protein language models, or other deep learning architectures) - A track record of shipping computational tools or pipelines that biologists actually use - Comfortable navigating ambiguity and defining problems in a rapidly evolving research environme

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the RL Teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.6 and Opus 4.6. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to safely write correct, fast code for accelerators. You'll need to know accelerator performance well to turn it into tasks and signals models can learn from. Specifically, you will: - Invent, design and implement RL environments and evaluations. - Conduct experiments and shape our research roadmap. - Deliver your work into training runs. - Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic. You may be a good fit if you: - Have expertise with accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch). - Have worked across the stack – kernels, model code, distributed systems. - Know how to balance research exploration with engineering implementation. - Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have: - Experience with reinforcement learning. - Experience porting ML workloads between different types of accelerators. - Familiarity with LLM training methodologies. The annual compensation range for this role is listed below. For sales roles, the range provided is th

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic is an AI safety and research company. We build reliable, interpretable, and steerable AI systems, and we believe AI will have a vast impact on the world — our goal is to ensure that impact is positive. About the role Anthropic is compute-constrained, and how we allocate that compute is one of the highest-leverage decisions we make as a company. Today, allocation choices are only loosely tied to the user outcomes we ultimately care about — retention, lifetime value, and the experience of people relying on Claude. This role exists to change that by addressing two intertwined problems at the heart of how we allocate compute. The first is an allocation problem: matching a volatile, heterogeneous stream of demand to a finite, heterogeneous fleet of chips. Which models run on which hardware, in which regions, under what serving configurations — with demand shifting and capacity bounded — is a problem the team navigates continuously today, with more intuition than rigor. You will bring structure to it: building the metrics and analytical frameworks that make the trade-offs legible, and partnering with the infrastructure teams that own these systems to turn that understanding into better decisions. The second is a causal-inference problem: there are many levers — rate limits, pricing, cache behavior, capacity shifts, routing changes — and only a partial picture of what pulling each one actually does to the users on the other end. You will build the causal understanding that closes that gap, choosing whatever approach the question calls for, so allocation decisions are made on expected user impact rather than intuition. This role is a fit for someone who thinks natively in terms of constrained allocation and queueing, who treats "what would happen if we changed X" as an identification problem rather than a dashboard query, and who wants their work to translate into operational and productionized change. You will work closely with the infrastructure engineers who run our compute, and your findings will be presented to senior leadership. Key responsibilities - Build and run testing frameworks — observational and synthetic — to quantify how different inputs affect compute allocation outcomes - Connect compute allocation decisions to downstream user outcomes (retention, lifetime value, revenue) - Partner closely with infrastructure engineers, product, and research to instrument systems, measure what matters, and ship operational changes - Develop the metric hierarchies, dashboards, and reporting that turn supply decisions into shared understanding across the company - Contribute analyses and recommendations to executive forums, and co-author the supply narrative shared with the CTO and staff Minimum qualifications - Strong technical individual-contributor background in data science, analytics, or operations research - Demonstrated comfort reasoning about resource allocation and trade-offs under constraints — drawn to systems problems, not just dashboards - Working fluency with causal inference — able to recogni

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Apply using this link . Applications for the next cohort of Anthropic Fellows close at 11:59pm PT on July 26 . The cohort is expected to start November 2 . In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the November start date doesn't work for you. Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect - 4 months of full-time research - Direct mentorship from Anthropic researchers - Access to a shared workspace (in either Berkeley, California or London, UK) - Connection to the broader AI safety and security research community - Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) - Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams. Some of t

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking an Engineering Manager, GRC to join our GRC organization and build the technical foundation for how we scale our risk and compliance programs. In this role, you will lead the team that designs and implements automated workflows, data pipelines, and integrations that transform manual compliance processes into scalable engineering systems. This is a greenfield opportunity to establish the team, architecture, and integrations that will define how we approach governance, risk, and compliance at Anthropic. The core challenge is a data problem: compliance information lives across dozens of systems—cloud infrastructure, identity providers, HR platforms, ticketing tools, code repositories—and your job is to design systems that bring it together, normalize it, and make it actionable. Success in this role comes from understanding how systems connect and how data flows between them. At Anthropic, you'll also have a unique advantage: the ability to design AI-powered workflows where Claude acts as an extension of your team, handling tasks that would traditionally require additional headcount or manual effort. You'll need ingenuity to identify where agentic AI can accelerate evidence collection, interpret unstructured data, triage compliance gaps, and augment human judgment in risk assessments. Working closely with Security, IT, and Engineering teams, you'll translate compliance and regulatory requirements into solutions that support audit programs including SOC 2, ISO, HIPAA, and FedRAMP, building systems that combine traditional automation with AI capabilities to achieve scale that wouldn't otherwise be possible. Key responsibilities - Lead the team that establishes foundational GRC processes and architecture. Design and build automated workflows for risk management and compliance, creating scalable systems that enable continuous monitoring as Anthropic grows. - Build data pipelines that aggregate risk, control, and asset information from across our technology stack. This means solving hard data integration problems: mapping disparate schemas, handling inconsistent data quality, and creating unified views of compliance posture through dashboards and reporting tools. - Inform GRC platform strategy and implementation: in partnership with other programs, plan for and build tooling that meets our compliance requirements. - Translate written policies and compliance requirements into policy-as-code—working with Engineering and Security teams to express requirements as enforceable rules, automated checks, and continuous validation rather than static documents. - Establish feedback loops between policy and implementation: surface where technical controls diverge from written requirements, identify where policies need to evolve based on infrastructure realities, and ensure that compliance requirements are expressed in terms engineers can act on. - Design and deploy agentic AI workflows that extend team capacity, using Claude to serve as a virtual GRC analyst to automate evidence analysis, monitor control effectiveness, draft audit responses, interpret policy documents, and handle other tasks that require reasoning over unstructured information. <

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs. As a Research Engineer on the team, you'll build and improve the core platform that underpins how we do RL at Anthropic, removing bottlenecks that slow down research and making it easier for the broader org to ship better models faster. This is high-leverage work: small improvements to velocity compound across every researcher and every run. Responsibilities - Build and improve the RL training infrastructure that researchers depend on day-to-day - Identify and remove bottlenecks across the RL stack: debugging, profiling, and rearchitecting where needed - Partner closely with researchers and with adjacent engineering teams (inference, sandboxing, and many more) to understand pain points and ship tooling that makes them faster - Own the reliability and performance of research runs end-to-end - Contribute to design decisions that shape how Anthropic does RL at scale You may be a good fit if you - Have strong software engineering fundamentals and a track record of building performant, reliable systems - Have worked on ML infrastructure, distributed systems, or research tooling - Care about enabling other people's work and find leverage through platforms rather than individual experiments - Are comfortable operating across the stack, from low-level performance work to RL algorithms - Have a bias toward shipping and iterating quickly, with a mix of high agency and low ego Strong candidates may also have - Experience with large-scale distributed training (RL, pre-training, or post-training) - Familiarity with JAX, PyTorch, or similar ML frameworks - A track record of operating at the edge of research and infra in a fast-moving environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: </strong&

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are looking for ML Engineers and Research Engineers to help detect and mitigate misuse of our AI systems. As a member of the Safeguards ML team, you will build systems that identify harmful use—from individual policy violations to sophisticated, coordinated attacks—and develop defenses that keep our products safe as capabilities advance. You will also work on systems that protect user wellbeing and ensure our models behave appropriately across a wide range of contexts. This work feeds directly into Anthropic's Responsible Scaling Policy commitments. Responsibilities - Develop classifiers to detect misuse and anomalous behavior at scale. This includes developing synthetic data pipelines for training classifiers and methods to automatically source representative evaluations to iterate on - Build systems to monitor for harms that span multiple exchanges, such as coordinated cyber attacks and influence operations, and develop new methods for aggregating and analyzing signals across contexts - Evaluate and improve the safety of agentic products—developing both threat models and environments to test for agentic risks, and developing and deploying mitigations for prompt injection attacks - Conduct research on automated red-teaming, adversarial robustness, and other research that helps test for or find misuse You may be a good fit if you - Have 4+ years of experience in ML engineering, research engineering, or applied research, in academia or industry - Have proficiency in Python and experience building ML systems - Are comfortable working across the research-to-deployment pipeline, from exploratory experiments to production systems - Are worried about misuse risks of AI systems, and want to work to mitigate them - Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders Strong candidates may also have experience with - Language modeling and transformers - Building classifiers, anomaly detection systems, or behavioral ML - Adversarial machine learning or red-teaming - Interpretability or probes - Reinforcement learning - High-performance, large-scale ML systems The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $350,000 - $500,000 USD Logistics Minimum education: Bac

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Sales Manager at Anthropic, you’ll lead a team of Strategic Account Executives driving the adoption of safe, frontier AI by winning and growing the world’s largest global systems integrators and consultancies — as both strategic customers and go-to-market partners. You’ll leverage your leadership and consultative sales expertise to propel revenue growth while developing a high-performing team of AEs. Working closely with Applied AI Engineering, Partnerships, and Product teams, you’ll help partners embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM and Marketing teams, you’ll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. The ideal candidate will have a passion for developing people, identifying market opportunities, and executing strategies to capture them. By leading the deployment of Anthropic’s emerging products, you will help systems integrators and their clients obtain new capabilities while also advancing the ethical development of AI. Responsibilities: - Recruit, coach, and retain Strategic Account Executives with deep partner/alliance and platform-selling expertise; develop leadership talent and create career paths that keep top performers growing - Codify the use cases, proof points, reference stories, and sales motions that make wins repeatable across each GSI partner and across both the sell-to and co-sell motions, partnering with Marketing, Enablement, Partnerships, and the partners themselves to scale them - Engage personally with C-level executives at the GSIs — and, on co-sell pursuits, at their enterprise clients — building business cases and value narratives and navigating complex procurement, security, and legal processes through to production deployment and expansion - Own the organization's revenue targets and operating rhythm, instilling pipeline-generation discipline and running forecasting, deal inspection, and account planning cadences that make performance predictable and coachable across both the internal-adoption and co-sell pipeline - Partner closely with Applied AI, Solutions Architecture, and Product to design solutions, prove value quickly, and translate partner and client needs into product and roadmap input - Orchestrate cross-functional and partner motions with Customer Success, Marketing, Partnerships (PAMs), Legal, and cloud partners to deliver a seamless experience, and represent Anthropic with partners and at industry events as a visible, trusted leader You may be a good fit if you have: - Experience leading strategic sales teams that sell technical, complex products such as API-first platforms, cloud infrastructure, or data and machine learning platforms - A track record of winning and growing strategic customers and/or partners, including building C-suite relationships, ideally with global systems integrators, consultancies, or other large partner/alliance ecosystems - Experience designing go-to-market coverage for a strategic sales team, including account and partner prioritization - Operational rig

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, governments, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences. About the Role We're looking for a Partnerships Manager to drive forward the clinical AI research agenda for Anthropic's global health work — informing the tools that bring Claude safely into care and generating the evidence that proves they work. You'll help define how clinical AI tools should be validated for use in low- and middle-income countries (LMICs), and you'll help shape the tools and safeguards that make Claude safe and usable in clinical settings. This is a hands-on role as much as a research one: you'll work side by side with Anthropic's research, evals, and product teams, translating what you know from how care actually gets delivered in low-resource settings into evaluations, safeguards, and product improvements. You'll join a small, tight-knit global health team within Beneficial Deployments. While you'll lead on this domain, you should expect to roll up your sleeves on adjacent workstreams, help shape overall team strategy, and be a thought partner to colleagues working on other parts of the health system. Everyone on the team owns the whole mission, not just their lane. Key responsibilities - Own the clinical research and evaluation agenda for our global health work — define what we need to prove, to what standard, and with whom, and drive it. - Design clinical evaluations and validation frameworks for LLMs in LMIC contexts, covering accuracy, safety, multilingual performance, and real-world conditions, in close partnership with Anthropic's research, evals, and product teams. - Develop theories of change and outcome metrics connecting model capability to care quality, health-worker performance, and patient outcomes. - Build and manage our global research partnerships, and engage with relevant regulatory and normative bodies (WHO, national authorities, research-ethics bodies). - Partner with internal research and product teams to improve Claude for clinical use cases in low-resource settings. Stay grounded in how care is actually delivered in LMICs so our tools and evaluations reflect those realities. - Contribute across the broader global health portfolio — lean in on adjacent workstreams, help set strategy, and be a thought partner to the team. Minimum qualifications - Medical training and clinical practice (MD, GP, MBBS, DO, or equivalent), with direct experience delivering care in low-resource settings — you reason fluidly from how diagnosis, triage, treatment, and referral actually happen at the point of care in low and middle income countries. - A concrete, on-the-ground understanding of clinical and care-delivery workflows in LMIC

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Computer Use team focuses on teaching Claude to see, use, and understand computer interfaces. As a Research Engineer on the team, you'll work on advancing our models' ability to reliably and safely operate real software. We're looking for someone who's genuinely excited about both the research and the product sides of computer use. Your work will translate directly into model improvements in our own and our customers' products. You can try Claude's computer use capabilities today through the Claude in Chrome extension and Claude Cowork. Key Responsibilities: - Design and run experiments to improve Claude's perception and agentic capabilities - Develop robust, reliable evaluation frameworks for measuring our models' ability to complete complex computer tasks - Build and improve computer use and vision reinforcement learning training environments - Create pipelines and tools to test and validate complex RL environments - Collaborate with teams across the model training and infrastructure stack to improve our production training setup - Partner with product teams to bring research advances into production Minimum Qualifications: - Software engineering experience and proficiency in Python - Experience training, fine-tuning, or evaluating machine learning models - Strong communication skills and a collaborative working style - Care about the societal impacts and safety of your work Preferred Qualifications: - Experience training models for computer use or other agentic capabilities - Experience with reinforcement learning, particularly in long-horizon or sparse-reward settings - Familiarity with multimodal model training - Experience building evaluations or benchmarks for agentic systems - Experience building reinforcement learning environments, simulation systems, or large-scale ML infrastructure - Experience working closely with product teams to drive model improvements The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 - $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experie

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the RL teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Fable 5 and Opus 4.8. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at. You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will: - Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization. - Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards. - Conduct experiments and shape our roadmap. - Deliver your work into research and production training runs. - Collaborate with other researchers and engineers across and outside Anthropic. You may be a good fit if you: - Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs. - Are fluent with industry EDA tools and processes. - Have taped out chips and have experience going from spec to silicon. - Know how to balance research exploration with engineering implementation. - Are passionate about AI's potential and committed to developing safe and beneficial systems. Strong candidates may also have: - Experience with reinforcement learning, evaluations or environments. - Built tooling or automation around chip design flows. - Worked on ML accelerators or high-performance compute hardware. - Familiarity with high-level synthesis or architecture simulators. </ul&

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As an Economist at Anthropic, you will work to measure and understand AI's effects on the global economy. You will make fundamental contributions to the development of the Anthropic Economic Index, establishing new methodologies to measure the usage, diffusion, and impact of AI throughout the economy using privacy-preserving tools and novel data sources. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions. Our team combines rigorous empirical methods with novel measurement approaches. We're building first-of-its-kind datasets tracking AI's impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system ( Clio ), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks. Responsibilities - Make fundamental contributions to the development and expansion of the Anthropic Economic Index , including quarterly reports and industry-specific deep dives - Design and conduct empirical research on AI's economic effects, drawing on external data sources and the privacy-preserving measurement systems internally - Develop new methodological approaches for studying AI's impact on: - Labor markets and the future of work - Productivity and task transformation - Economic inequality and displacement - Industry-specific disruption and adaptation - Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios - Develop causal-inference tooling — e.g. surrogate indexes, heterogeneous-effect pipelines — to help Anthropic evaluate the downstream economic consequences of its own compute, product, and pricing decisions - Build and maintain relationships with academic institutions, policy think tanks, and other research partners - Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection - Translate research insights into actionable recommendations for both product decisions and policy discussions - Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders You May Be a Good Fit If You Have - PhD in Economics - Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning - Experience relevant to the study of AI’s impact on the economy, including: - Labor market analysis and occupational change - Task-based appr

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Note: we don't have open Research Manager positions on the Interpretability team at this time. However, we're actively growing our team of Research Engineers and Research Scientists . If you're excited about interpretability research and open to an individual contributor role, we encourage you to apply. About the Interpretability team When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team’s mission is to reverse engineer how trained models work, and Interpretability research is one of Anthropic’s core research bets on AI safety. We believe that a mechanistic understanding is the most robust way to make advanced systems safe. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks, or as treating neural networks as binary computer programs we're trying to "reverse engineer". We aim to create a solid scientific foundation for mechanistically understanding neural networks and making them safe (see our vision post ). We have focused on resolving the issue of "superposition" (see Toy Models of Superposition , Superposition, Memorization, and Double Descent , and our May 2023 update ), which causes the computational units of the models, like neurons and attention heads, to be individually uninterpretable, and on finding ways to decompose models into more interpretable components. Our subsequent work which found millions of features in Claude 3.0 Sonnet, one of our production language models, represents progress in this direction. In our most recent work , we developed methods that allow us to build circuits using features and use these circuits to understand the mechanisms associated with a model's computation and study specific examples of multi-hop reasoning, planning, and chain-of-thought faithfulness on Claude Haiku 3.5, one of our production models.” This is a stepping stone towards our overall goal of mechanistically understanding neural networks. A few places to learn more about our work and team are this introduction to Interpretability from our research lead, Chris Olah, Stanford CS25 lecture given by Josh Batson, and TWIML AI podcast with E

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be account compromise: Anthropic's enforcement systems have to distinguish customers whose accounts have been compromised from actors abusing the platform — and today those two populations can look identical in the data. Stolen credentials and leaked keys are a growing abuse vector, and the collateral damage from enforcement against them lands on legitimate users. You'll own this problem end to end: detection, revocation, user notification, remediation, and the criteria for restoring access — turning what is today ad hoc incident response into a scalable, repeatable program. This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Key responsibilities - Investigate credential-compromise incidents across first-party and third-party platforms, tracing actor behavior across accounts and surfaces - Design and operate remediation workflows for compromised accounts: revocation, customer notification, and standards for restoring access - Partner with Engineering and Data Science teams to improve how we separate compromised-customer traffic from willful abuse - Enforce usage policies with a focus on detecting and mitigating potentially harmful use of AI systems - Work with threat intelligence on emerging credential-abuse patterns and the actors behind them - Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios - Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows - Write the policy framework for compromise scenarios, including cases where Anthropic can't independently verify a customer's security posture - Act as the enforcement SME when account compromise intersects with active abuse investigations Minimum qualifications - Experience in trust and safety, fraud investigation, security operations, or a related field - Subject matter expertise in one or more of: account takeover, credential abuse, session security, or incident response - Experience designing or operating enforcement, remediation, or customer-recovery flows — not just detection - Comfort using data (SQL or similar tools) to trace actor behavior across accounts and to measure what's working - A thoughtful perspective on the tension between protecting the platform and restoring access for legitimate compromised customers - Strong written communication skills, with experience producing clear briefs about messy incidents for technical and non-technical stakeholders - Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and work

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the teams Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas: - Developing systems that enable models to use computers effectively - Advancing code generation through reinforcement learning - Pioneering fundamental RL research for large language models - Building scalable RL infrastructure and training methodologies - Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to both implement novel approaches and contribute to the research direction. You'll work on fundamental research in reinforcement learning, creating 'agentic' models via tool use for open-ended tasks such as computer use and autonomous software generation, improving reasoning abilities in areas such as mathematics, and developing prototypes for internal use, productivity, and evaluation. Representative projects: - Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters. Help scale our systems to handle increasingly complex research workflows. - Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents which push the state of the art for the next generation of models. - Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows. - Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research. You may be a good fit if you: - Are proficient in Python and async/concurrent programming with frameworks like Trio - Have experience with machine learning frameworks (PyTorch, TensorFlow, JAX) - Have industry experience in machine learning research - Can balance research exploration with engineering implementation&lt

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Safeguards Policy Analyst focused on Fraud & Scams, you will be responsible for designing, building, and executing enforcement workflows that detect and mitigate fraud and scam-related harms on Anthropic's products. You will serve as the subject matter expert on fraud typologies, scam ecosystems, and the threat actors who perpetrate them — translating that expertise into durable and scalable policies. This role sits within the Integrity & Authenticity (I&A) team, You will function both as a policy owner, and work closely with threat investigative and enforcement teams. You will also develop the guidelines that power classifiers, and will be our point of content cross-functional workstreams. No two days will look the same. Important context: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a financial, psychological, or otherwise disturbing nature, including detailed fraud schemes and scam content. Responsibilities: Policy Design & Ownership - Draft, maintain, and iterate on Fraud & Scams policies governing Anthropic's products and APIs, with clarity for both model enforcement and human reviewers - Conduct regular structured policy reviews to identify gaps, ambiguities, and coverage failures, and lead the process to close them - Develop detailed threat models for fraud and scam vectors — including social engineering, financial fraud, impersonation scams, phishing, and AI-enabled fraud — and translate these into enforceable policy language - Stay current on the fraud and scam landscape, including emerging typologies, regulatory shifts, and threat actor tactics, techniques, and procedures (TTPs) Enforcement Strategy & Operations - Design and architect automated enforcement systems and human review workflows that scale effectively while maintaining high precision and recall - Review flagged content to drive enforcement decisions and surface policy improvements grounded in real-world cases - Define and manage precision/recall tradeoffs in enforcement, working with data science teams to continuously tune classifiers and detection signals - Build and maintain an effective feedback loop between threat intelligence, policy, and enforcement operations to ensure timely response to novel and evolving fraud threats Technical & Cross-functional Collaboration - Serve as the primary policy point of contact for ML and Engineering teams developing fraud detection classifiers, working to translate policy intent into technical artifacts and training signals - Partner with Product, Engineering, and Data Science teams to optimize detection models, automated enforcement pipelines, and tooling for fraud-specific policy violations - Collaborate with external researchers, law enforcement liaisons, and fraud SMEs to gather feedback on policy effectiveness and emerging ris

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is building Treasury with scale and automation in mind from the start. We're creating modern, well-controlled processes that can grow with the business - supported by strong systems, clear governance, and practical use of AI-enabled tools. We're designing AI-native workflows from day one, with human in the loop, SOX-grade controls built in rather than bolted on. This role reports to the Treasury Ops Lead and owns the company's global cash and liquidity function. You'll run the daily cash desk - positioning, forecasting, funding, and payments, while building the visibility and liquidity structures (pooling, concentration, repatriation) that let a multi-entity, multi-currency company see and deploy its cash as one balance sheet. This is a hands-on role for someone who enjoys both execution and process building. You should be comfortable running the daily position while designing the cash architecture the company will run on at 10x scale. Key responsibilities - Own daily cash positioning across all entities and currencies, track balances, consolidate activity, and set the daily funding plan - Direct cash management operations: wire/ACH execution, cash concentration, sweep structures, and cash pooling activities - Build and run the short- and medium-term cash forecast (13-week and beyond), including variance tracking, scenario modeling, and reporting to leadership - Identify and implement strategies to optimize working cash balances and minimize idle funds - right cash, right entity, right currency, right time - Monitor liquidity risk, counterparty exposure, and concentration limits; escalate before they become issues - Build a single global view of cash - consolidate balance and transaction reporting across all banks, entities, and currencies into one source of truth - Partner with the Accounting team to design and manage intercompany funding and settlement processes, including cross-border movement, netting, and documentation - Streamline cross-border transaction flows and optimize cash repatriation strategies in partnership with Accounting, Tax, and Legal - Support pooling / in-house-bank structures as the entity footprint grows - Manage bank relationships from the services side including fee analysis, service reviews, wallet allocation, and connectivity - to get the most out of our banking partners - Design the "Claudification" layer for cash: identify which workflows to be automated, build the automation, keep humans in the decisions that need judgment - Support TMS buy vs build evaluation/implementation with a cash-and-liquidity lens: bank connectivity (SWIFT, APIs, host-to-host), balance/transaction reporting, cash-position and forecast modules - Partner with Finance Systems to simplify and automate cash reporting and forecasting - Own cash and liquidity data quality - the source of truth that positioning, forecasting, and investment decisions depend on - Execute cash processes with strong focus on controls, documentation, segregation of duties, and audit readiness - Support development and maintenance of

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role: We are seeking a People Research Scientist to join our People Data Solutions team. You’ll be the research expert supporting our broader People organization, using rigorous scientific methods to advance our understanding of the employee experience, manager effectiveness, organizational health, and workforce dynamics. This role sits at the intersection of organizational science, behavioral research, and people strategy – developing novel frameworks and conducting systematic research that drives evidence-based people decisions across our growing organization. This role offers the opportunity to make a significant impact on both our people practices and the broader field of people science at a leading AI safety company. Responsibilities: Research Design & Scientific Inquiry - Design and execute systematic research studies to answer fundamental questions about employee experience, manager effectiveness, and organizational health - Generate and test hypotheses about people programs, employee behavior, and workforce outcomes using rigorous experimental and quasi-experimental methods - Conduct longitudinal studies tracking employee cohorts to understand long-term workforce trends and the impact of people initiatives - Perform meta-analyses of people interventions across the industry to identify best practices and knowledge gaps - Navigate research ethics considerations when studying employee data, ensuring responsible research practices Employee listening & survey research - Design, analyze, and iterate on employee listening programs including engagement surveys, pulse surveys, and lifecycle surveys - Apply psychometric methods to validate survey instruments and ensure measurement reliability - Translate survey findings into strategic recommendations that drive meaningful organizational change Manager research & organizational effectiveness - Conduct research on manager behaviors, competencies, and their impact on team outcomes - Build measurement frameworks to evaluate and improve manager effectiveness programs - Study organizational dynamics including team composition, collaboration patterns, and their relationship to performance outcomes Visualization & communication - Build compelling visualizations and dashboards that make complex research findings accessible to diverse audiences - Present research findings to senior leadership with clear, actionable recommendations - Develop self-service analytics capabilities that empower People team partners Minimu

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's RL Scaling Science team studies how reinforcement learning behaves as we scale it (across model size, compute, and task horizon) and turns that understanding into the training recipes behind our frontier models. As a Research Engineer on this team, you'll design and run large-scale experiments to understand and resolve bottlenecks, build the benchmarks that make long-horizon progress measurable, and ship validated findings directly into production training. This role lives at the boundary between research and engineering. The problems are open, the experiments run at frontier scale, and the path from a robust result to production is short. Key responsibilities - Design, run, and interpret large-scale RL experiments, reasoning rigorously about what the data does and doesn't show - Investigate how RL improves as horizon, compute, and model size grow - Build and maintain benchmarks for long-horizon RL so progress is measurable and reproducible - Translate validated findings into production training recipes, exercising judgment about when a result is robust enough to ship - Debug complex issues at the seam where research meets infrastructure - failures that only appear at scale - Partner closely with adjacent RL teams across research and engineering and advance our overall RL stack Minimum qualifications - Strong empirical research skills in Reinforcement Learning, large-scale ML training, or a closely adjacent area - Demonstrated ability to own large experiments end-to-end, from design through interpretation - Proficiency in Python and experience working with large-scale or distributed ML systems - Comfort operating at the research/systems boundary, including debugging where the two meet - Care about the societal impacts of AI and responsible scaling Preferred qualifications - Published or shipped work in long-horizon RL or RL fundamentals - Experience translating research findings into production training recipes - Demonstrated large scale industry impact via RL interventions - Experience working on frontier-scale training runs with long trajectories Representative projects - Design a benchmark suite for long-horizon RL that distinguishes genuine capability gains from artifacts of evaluation setup - Take a promising experimental finding, stress-test it across model scales, and work with training teams to land it in a production recipe - Investigate an unexpected scaling trend in an RL run and trace it to a root cause spanning algorithm, data, and infrastructure The annual compensation range for this role is listed below. </p

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. We’re looking for researchers and engineers to join our efforts. People mean many different things by "interpretability". We're focused on mechanistic interpretability, which aims to discover how neural network parameters map to meaningful algorithms. Some useful analogies might be to think of us as trying to do "biology" or "neuroscience" of neural networks using “microscopes” we build, or as treating neural networks as binary computer programs we're trying to "reverse engineer". A few places to learn more about our work and team at a high level are this introduction to Interpretability from our research lead, Chris Olah ; a discussion of our work on the Hard Fork podcast produced by the New York Times, and this blog post (and accompanying video) sharing more about some of the engineering challenges we’d had to solve to get these results. Some of our team's notable publications include A Mathematical Framework for Transformer Circuits , In-context Learning and Induction Heads , Toy Models of Superposition , Scaling Monosemanticity , and our Circuits’ Methods and Biology papers. This work builds on ideas from members' work prior to Anthropic such as the original circuits thread , Multimodal Neurons , <a class="text-accent-seco

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As part of our growing Data Science & Analytics team, you will play an instrumental role in Anthropic's mission of building safe and beneficial AI — this time by driving data-informed decisions across the commercial customer lifecycle. This role sits at the intersection of fast-moving sales operations and rigorous statistical analysis. You will work across multiple segments and products, partnering with analytics engineers, fellow data scientists, and go-to-market leadership to turn complex commercial data into actionable strategy. You will own measurement and analysis for new logo acquisition through activation, expansion, and retention for a rapidly scaling, consumption-based AI platform. You've worked in cultures of analytical rigor before, and you're eager to help shape the norms and best practices of a growing data science function at a pivotal moment in the company's growth. Key responsibilities - Define key metrics, build measurement frameworks, and maintain core reporting to evaluate GTM success across segments and products - Analyze commercial and user data to surface actionable insights, size opportunities, and influence roadmaps and go-to-market strategy - Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to make clear, actionable recommendations - Investigate anomalies, conduct root cause analyses, and provide data-driven guidance on priorities and decisions - Build statistical models, optimization frameworks, and simulations to support and automate commercial decision-making processes - Present analyses and recommendations to both technical and non-technical stakeholders, including GTM leadership - Establish foundational data practices and help scale analytics infrastructure to support rapid product and commercial iteration Minimum qualifications - Proficiency in Python, SQL, and data visualization tools - Expertise in experimental design, causal inf

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Apply using this link . Applications for the next cohort of Anthropic Fellows close at 11:59pm PT on July 26 . The cohort is expected to start November 2 . In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the November start date doesn't work for you. This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting . Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect - 4 months of full-time research - Direct mentorship from Anthropic researchers - Access to a shared workspace (in either Berkeley, California or London, UK) - Connection to the broader AI safety and security research community - Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) - Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research progra

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Apply using this link . Applications for the next cohort of Anthropic Fellows close at 11:59pm PT on July 26 . The cohort is expected to start November 2 . In some circumstances, we can accommodate fellows starting outside the usual cohort timelines — please note in your application if the November start date doesn't work for you. This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting . Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect - 4 months of full-time research - Direct mentorship from Anthropic researchers - Access to a shared workspace (in either Berkeley, California or London, UK) - Connection to the broader AI safety and security research community - Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) - Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research progra

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Strategic Account Executive focused on cybersecurity, you'll own some of Anthropic's most strategic cybersecurity relationships—companies building the next generation of AI-powered security products. These aren't typical enterprise accounts; they're partners shaping how AI transforms the entire security industry. You'll drive multi-million dollar commitments by expanding Claude's footprint across customer product portfolios (AI-powered SOC, threat detection, security copilots) and internal operations (Claude Code for engineering teams). You'll work at the intersection of executive relationships and technical depth—one week you're in a CTO strategy session, the next you're helping an engineering team scope an agentic deployment. This role requires someone who can think like a partner, not just a seller. You'll collaborate closely with our Applied AI team on custom deployments, work with Product on cybersecurity-specific capabilities, and help shape Anthropic's go-to-market in one of our highest-potential verticals. Responsibilities: - Win business and drive revenue within a book of strategic cybersecurity accounts.Own the full sales cycle from prospecting to close - Drive expansion across multiple buying centers within strategic accounts—product teams building customer-facing AI features, platform teams deploying Claude Code to engineering orgs, and security research teams exploring frontier capabilities - Navigate complex organizational structures across security, product, engineering, and executive teams. Build multi-threaded relationships with CISOs, security architects, product and engineering leaders, and C-suite executives - Partner with Solutions Architect and Product teams on technical scoping, custom agent development, and enterprise deployments - Design and execute innovative sales strategies tailored to the cybersecurity market. Analyze account landscape, competitive dynamics, and emerging security trends to inform targeted sales activities - Identify and develop use cases across security operations (SecOps automation, threat hunting, alert triage), security product development (AI-powered detection, intelligent response), and internal security functions - Navigate unique considerations of AI in security contexts, including model guardrails, responsible deployment, and emerging use cases like AI red-teaming - Own sophisticated deal cycles involving security evaluations, red team assessments, and complex procurement processes. Navigate security and compliance requirements with patience and expertise - Build and maintain accurate pipeline forecasting for complex, multi-workstream accounts. Develop deep understanding of how large security vendors budget for AI infrastructure across product and internal use cases - Serve as the voice of the cybersecurity customer internally. Inform product roadmaps by gathering feedback on security-specific requirements, compliance needs, and competitive gaps

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Analyst focusing on Integrity & Authenticity, you will be responsible for building and executing enforcement workflows for our products and services, with a focus on detecting and mitigating attempts to misuse Anthropic's AI systems for coordinated inauthentic behavior, election manipulation, and targeting, tracking, and surveillance of individuals. Your work will span a broad and interconnected set of harm areas: AI-enabled influence operations and disinformation campaigns, the abuse of AI to interfere with electoral processes, and the use of AI systems to facilitate stalking, surveillance, profiling, and the targeting of individuals or groups. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a political, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays, particularly around major electoral events. Key responsibilities - Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy - Partner with Engineering and Data Science teams to optimize detection models for policy violations and automated enforcement systems - Review flagged content to drive enforcement and policy improvements - Enforce usage policies with a focus on detecting and mitigating AI-enabled influence operations, coordinated inauthentic behavior, election interference, and targeting, tracking, or surveillance of individuals and groups - Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios - Keep up to date with emerging AI policy enforcement best practices, evolving threat actor tactics, and the regulatory landscape around elections, privacy, and surveillance, using these to inform our decision-making and workflows Minimum qualifications - Experience in trust & safety, policy enforcement, threat intelligence, or a closely related field with a focus on one or more of: influence operations, disinformation, coordinated inauthentic behavior, election integrity, or privacy and surveillance harms - Experience standing up and scaling policy enforcement or content review workflows - Proficiency in SQL and/or other data analysis tools to draw insights from large datasets - Experience identifying emerging risks and threat actors, and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams - Experience working with generative AI products, including writing effective prompts for content review and enforcement - Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space Preferred qualifications - Experience conducting cross-platform i

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are looking for biological scientists to help build safety and oversight mechanisms for our AI systems. As a Safeguards Biological Safety Research Scientist, you will apply your technical skills to design and develop our safety systems which detect harmful behaviors and to prevent misuse by sophisticated threat actors. You will be at the forefront of defining what responsible AI safety looks like in the biological domain, working across research, policy, and engineering to translate complex biosecurity concepts into concrete technical safeguards. This is a unique opportunity to shape how frontier AI models handle dual-use biological knowledge—balancing the tremendous potential of AI to accelerate legitimate life sciences research while preventing misuse by sophisticated threat actors. In this role, you will: - Design and execute capability evaluations ("evals") to assess the capabilities of new models - Collaborate closely with internal and external threat modeling experts to develop training data for our safety systems, and with ML engineers to train these safety systems, optimizing for both robustness against adversarial attacks and low false-positive rates for legitimate researchers - Analyze safety system performance in traffic, identifying gaps and proposing improvements - Develop rigorous stress-testing of our safeguards against evolving threats and product surfaces - Partner with Research, Product, and Policy teams to ensure biological safety is embedded throughout the model development lifecycle - Contribute to external communications, including model cards, blog posts, and policy documents related to biological safety - Monitor emerging technologies for their potential to contribute to new risks and new mitigation strategies, and strategically address these Minimum Qualifications: - A PhD in molecular biology, virology, microbiology, biochemistry, systems or computational biology, or a related life sciences field, OR equivalent professional experience - Extensive experience in scientific computing and data analysis, with proficiency in programming (Python preferred) - Deep expertise in modern biology, including both "reading" (e.g. high-throughput measurement, functional assays) and "writing" (gene synthesis, genome editing, strain construction, protein engineering) techniques in biology - Familiarity with dual-use research concerns, select agent regulations, and biosecurity frameworks (e.g., Biological Weapons Convention, Australia Group guidelines) - Strong analytical and writing skills, with the ability to navigate ambiguity and explain complex technical concepts to non-technical stakeholders - Have a passion for learning new skills and an ability to rapidly adapt to changing techniques and technologies - Comfort working in a fast-paced environment where priorities may shift as AI capabilities evolve Preferred Qualifications - Background in AI/ML systems, particularly experience with large language models - Experience in

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: When you see what modern language models are capable of, do you wonder, "How do these things work? How can we trust them?" The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe. Think of us as doing "neuroscience" of neural networks using "microscopes" we build - or reverse-engineering neural networks like binary programs. More resources to learn about our work: - Our research blog - covering advances including Monosemantic Features and Circuits - An Introduction to Interpretability from our research lead, Chris Olah - The Urgency of Interpretability from CEO Dario Amodei - Engineering Challenges Scaling Interpretability - directly relevant to this role - 60 Minutes segment - Around 8:07, see a demo of tooling our team built - New Yorker article - what it's like to work on one of AI's hardest open problems Even if you haven’t worked on interpretability before, the infrastructure expertise is similar to what's needed across the lifecycle of a production language model: - Pretraining: Training dictionary learning models looks a lot like model pretraining - creating stable, performant training jobs for massively parameterized models across thousands of chips - Inference: Interp runs a customized inference stack. Day-to-day analysis requires services that allow editing a model's internal activations mid-forward-pass - for example, adding a "steering vector" - Performance: Like all LLM work, we push up against the limits of hardware and software. Rather than squeezing the last 0.1%, we are focused on finding bottlenecks, fixing them and moving ahead given rapidly evolving research and safety mission The science keeps scaling - and it's now applied directly in safety audits on frontier models, with real deadlines. As our research has matured, engineering and infrastructure have become a bottleneck. Your work will have a direct impact on one of the most important open problems in AI. Responsibilities: - Build and maintain the specialized inference and training infrastructure that powers interpretability research - including instrumented forward/backward passes, activation extraction, and steering vector a

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Safeguards Engineering builds and operates the infrastructure that keeps Anthropic's AI systems safe in production — the classifiers, detection pipelines, evaluation platforms, and monitoring systems that sit between our models and the real world. That infrastructure needs to be not just correct, but reliable : when a safety-critical pipeline goes down or degrades, the consequences can be serious, and they can be invisible until someone looks closely. As a Technical Program Manager for Safeguards Infrastructure and Evals, you'll own the operational health and forward momentum of this stack. Your primary responsibility is driving reliability — owning the incident-response and post-mortem process, ensuring SLOs are defined and met in partnership with various teams, and making sure that when things go wrong, the right people know, the right actions get taken, and those actions actually get closed out. Alongside that ongoing operational rhythm, you'll coordinate the larger platform investments: migrations, eval-platform improvements, and the cross-team dependencies that connect them. This role sits at the intersection of operations and program management. It requires genuine technical depth — you need to understand how these systems work well enough to triage effectively, judge what's actually safety-critical versus what can wait, and have informed conversations with the engineers building and maintaining them. But the core of the job is keeping the machine running well and the work moving. What You'll Do: - Own the Safeguards Engineering ops review - Drive the recurring cadence that keeps the team informed and coordinated: surfacing recent incidents and failures, bringing visibility to reliability trends, and making sure the right people are in the room when decisions need to be made. This is the heartbeat of how Safeguards Eng stays ahead of operational risk. - Drive incident tracking and post-mortem execution - When incidents happen — and in this space, they happen regularly — you'll make sure they get followed through properly. That means tracking incidents across the organization (including those owned by partner teams like Inference), ensuring post-mortems get written, and most critically, making sure the action items that come out of them actually get done. Closing the loop on post-mortem actions is one of the highest-leverage things this role does. - Establish and maintain SLOs with partner teams - Work with Safeguards Engineering teams and key partners — particularly Inference and Cloud Inference — to define service-level objectives for safety-critical pipelines. Then build the tracking and reporting that makes it possible to tell whether those SLOs are being met, and surface it when they're not. - Maintain runbook quality and incident-ownership clarity - Safety-critical systems need clear playbooks for when things go wrong. Partner with engineering leads to keep runbooks accurate, actionable, and up to date — and ensure that ownership of incidents is unambiguous so that nothing falls through the cracks durin

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Safeguards team builds the systems that detect and mitigate misuse of our AI models, from individual policy violations to sophisticated, coordinated attacks. A growing part of that work depends on lightweight detection methods trained on model internals, which let us identify harmful behavior cheaply and at scale. This work feeds directly into Anthropic's Responsible Scaling Policy commitments. We're looking for an engineer to own the infrastructure behind that research. This is the tooling our researchers rely on to run experiments, train detection methods, and select detections for launch. It sits between research and production: researchers depend on it for fast iteration, and our detection systems depend on it for reliable, correct results as our models continue to change. Running machine learning workloads at our scale often requires solving novel systems problems. You'll identify those problems and build the abstractions, pipelines, and tooling that keep the research loop fast as requirements shift underneath you. Strong candidates will have a track record of solving large-scale systems and data problems and will be excited to grow deep machine learning expertise alongside it. Key responsibilities - Build and scale the infrastructure and data pipelines behind Safeguards machine learning research - Own the training, evaluation, and scoring workflows researchers use, with a focus on cutting the time between an idea and a result - Design tooling and interfaces, including libraries and command line tools, that researchers can use directly without needing to understand the systems underneath - Build correctness and sanity checking into the stack, so results stay trustworthy as models and workloads evolve - Take the highest-value research workflows from experiments to reliable, production-grade jobs - Improve the throughput, cost, and reliability of large-scale inference and scoring workloads - Partner closely with researchers and engineers across Safeguards to understand their workflows, anticipate how their needs will change, and design for that ahead of time Minimum qualifications - Strong software engineering fundamentals and hands-on coding ability, with proficiency in Python - Experience building and operating data-intensive or distributed systems in production - Experience building tooling or infrastructure that other engineers or researchers use as a dependency - Comfort working across the research-to-deployment pipeline, from exploratory experiments to production systems - Ability to debug performance and correctness problems across an unfamiliar stack - Strong written and verbal communication skills, and a collaborative approach to technical decisions Preferred qualifications - Experience with high-performance, large-scale machine learning systems - Familiarity with language modeling and transformers, including working with model internals - Experience

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking an exceptional Legal Program Manager to serve as the operational backbone of contracting for the Compute and Infrastructure team. We'll rely on you to manage a high volume of procurement and vendor agreements — including datacenter colocation, lease, and build-to-suit agreements; hardware, chip, and network-equipment procurement; and construction, facilities, and operations-and-maintenance (O&M) contracts — along with the NDAs, order forms, SOWs, and amendments that surround them. You will build the scalable contracting processes — templates, playbooks, intake and approval workflows, and contract lifecycle management — that let the business move at the speed of Anthropic’s infrastructure buildout. This role owns the system, throughput, and visibility that move every agreement from intake through signature. Key responsibilities - Coordinate and shepherd a high volume of compute and infrastructure procurement transactions — datacenter colocation, lease, and build-to-suit agreements; hardware, chip, and network-equipment procurement; construction/EPC and facilities/O&M agreements; and the supporting NDAs, order forms, SOWs, and amendments — driving each from intake through signature - Own and administer the contract lifecycle management system: workflow design and configuration, templates, approval routing, signing and archive and integrity hygiene - Design and run intake and triage: how requests enter, how they are prioritized, and how they route to the right owner - Propose and develop scalable solutions to improve contracting efficiency and throughput across the infrastructure vendor base - Collaborate with business units and legal team members to streamline contract management processes, manage post-signature obligations and renewals across the infrastructure vendor portfolio, identify potential risks, and drive continuous improvement in contract handling efficiency - Partner closely with the Compute and Infrastructure, Product, Finance, Security, Business Operations, and Procurement Ops teams to achieve key business objectives and deliver strategic, business-minded, and solutions-focused counsel - Build reporting, dashboards, SLAs, and the metrics that surface turnaround times and bottlenecks across the infrastructure vendor portfolio - Deploy LLM and AI tooling to scale contracting throughput and reduce manual handling Minimum Qualifications - Experience operating in a fast-paced technology startup in which priorities shift rapidly and schedules "move to the left," thriving in this dynamic environment and priding yourself on your adaptability and ability to pivot with speed and grace - Initiative and autonomy in managing complex contractual matters, effectively prioritizing competing deadlines - An understanding of what's important in the context of a contract, the organization's mission, and enough contract fluency to triage and route requests, track obligations, and pull in relevant legal counsel - Excitement to grow with an organization and help shape the culture of the commercial function - A prefe

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Anthropic's Life Sciences team is building a world-class research group focused on making fundamental biological discoveries. The team combines cutting-edge AI with hands-on biological research, positioning Anthropic at the forefront of AI-accelerated scientific discovery. About the role We're seeking an exceptional Research Scientist to join the team. As a founding member of Life Sciences, you'll work in a high-impact group that operates at the intersection of computational and experimental biology. You'll help establish Anthropic as a leader in biology research while developing product intuition through direct engagement with the challenges and opportunities of laboratory science. Key responsibilities - Design, execute, and iterate on the experimental programs at the core of the team's research: molecular biology, biochemistry, protein and nucleic acid characterization, high-throughput functional screens, and the assay development that makes new questions answerable - Partner directly with computational biologists to design experiments that produce high-quality, analysis-ready data, and feed results back fast enough to immediately inform the next round of analysis - Generate and prioritize hypotheses by combining your experimental judgment with the literature, curated biological knowledge bases, and the team's computational predictions - Use Claude and our internal agent frameworks heavily in your own work — for experimental planning, protocol development, and data interpretation — and feed what you learn back to the model-improvement and product teams as evaluations, datasets, and concrete failure cases Minimum qualifications - Have a Ph.D. in a biological science (molecular biology, biochemistry, bioengineering, computational biology) or a related field - Have a track record of bridging biological domain knowledge with computational approaches to solve real scientific problems - Have basic proficiency in Python and are familiar with ML development practices <h2 class="text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping customers understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your technical depth with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability. As a Commercial Solutions Architect, you'll go deep with priority accounts as a hands-on builder, while creating reusable blueprints, demos, and enablement that extend Claude's reach across the broader Commercial book of business. Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems. Responsibilities: - Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation - Serve as the primary technical advisor to customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams and stakeholders to drive customer success - Support customers building with the Claude API, Claude Code, and Claude for Enterprise - Ship working code. Build prototypes and proof-of-concepts hands-on, develop eval frameworks, and write near-production examples that customers can extend - Build reusable blueprints, demos, and enablement assets that scale across customers - Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack - Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases - Identify common integration patterns and contribute insights back to our Product and Engineering teams - Travel occasionally to customer sites for workshops, technical deep dives, and relationship building - Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns You may be a good fit if you have: - 3+ years of highly technical experience as a software engineer (or equivalent) with some customer-facing exposure, OR 3+ years as a Solutions Architect, Sales Engineer, or Technical Account Manager with strong hands-on building experience - A builder identity. You've shipped real software, you have technical taste, and you care about the craft of what