This role involves leading a team of Applied AI Architects to drive the adoption of Anthropic's AI products across Europe's fastest-growing tech companies. Responsibilities include managing the team, setting pre-sales standards, working with high-value customers, and representing Anthropic in the European tech community.
This role focuses on ensuring the reliability and resilience of large language model serving systems at scale. You'll design service level objectives, build observability tooling, lead incident response, and collaborate across teams to strengthen critical infrastructure paths—from API layers to accelerators. The position demands a systems-thinking engineer passionate about robustness, safety, and cross-team partnership in high-stakes AI environments.
This role involves conducting research and engineering to advance large language models, focusing on model architecture, optimization, and scalable training infrastructure. You'll work across the full stack—from low-level system optimizations to high-level model design—while contributing to scientific experiments and tooling. The position emphasizes collaboration, interpretability, and AI safety within a cohesive research team.
Design and build full-stack internal tools and platforms that empower non-technical users by identifying patterns in workflows and abstracting them into reusable systems. Work closely with stakeholders to define priorities, iterate on feedback, and ship features that drive autonomy across the organization. Use Python, TypeScript, and React in a high-impact, collaborative environment focused on AI safety and reliability.
Build and maintain foundational systems for AI safety, oversight, and intervention mechanisms, focusing on detecting unwanted model behaviors and preventing misuse. Develop infrastructure for data management, evaluation systems, and tooling for human and agentic review while ensuring high operational reliability at scale. Work closely with cross-functional teams to implement robust, multi-layered defenses in a safety-first AI environment.
This role involves building and optimizing the machine learning infrastructure that supports Anthropic’s reinforcement learning research. You'll work closely with researchers to improve training efficiency, debug performance bottlenecks, and develop tooling that accelerates model development. The position focuses on high-leverage platform improvements that scale across the entire research team.
This role involves designing and maintaining large-scale continuous integration infrastructure to support rapid, reliable code deployment across multiple cloud environments. The engineer will build intelligent test selection systems, improve CI reliability through flake detection and automation, and enhance developer productivity with scalable tooling. The position operates within a high-impact research and product environment focused on safe and steerable AI systems.
Engage in empirical research on AI's economic and societal impacts, supported by mentorship from Anthropic researchers. Work on a project using external data and tools to produce a public output such as a paper, with opportunities to contribute to policy-relevant insights. Collaborate within a multidisciplinary team focused on AI safety and societal resilience.
This role involves a 4-month, full-time research fellowship focused on ML systems and performance, with mentorship from Anthropic researchers. Fellows will work on empirical projects using external infrastructure to build scalable ML systems, debug training processes, and support high-performance computing environments. The program emphasizes collaboration, rapid implementation, and producing public research outputs such as papers.
This role involves conducting empirical economic research to understand AI's impact on labor markets, productivity, and economic transformation across a specific region. The economist will develop and expand the Anthropic Economic Index using novel measurement systems like Clio, applying advanced econometric and machine learning methods. They will collaborate with governments, academia, and policy institutions to translate research into actionable insights and influence both public policy and internal business decisions.
This role involves managing a team of Technical Deployment Leads (TDLs) in the Financial Services sector, ensuring high-quality delivery of AI solutions, and building strong relationships with executive stakeholders. Responsibilities include hiring, developing team members, managing customer engagements, and setting technical and operational standards.
Lead and build a sales team focused on driving adoption of AI systems within mission-driven organizations across Europe, the Middle East, and Africa. The role involves securing strategic partnerships with nonprofits, foundations, educational institutions, and social enterprises, while navigating complex stakeholder ecosystems, regulatory environments, and funding models. This is a player-coach position requiring hands-on deal closing, team development, and shaping of regional sales strategy in a rapidly evolving environment.
This role focuses on designing and operating large-scale AI infrastructure, specifically managing the lifecycle of compute nodes across cloud and on-prem environments. The engineer will lead technical strategy for node provisioning, health monitoring, and automated repair systems, ensuring high reliability and efficiency across Anthropic's GPU, TPU, and Trainium fleets. Collaboration with research, inference, and cloud provider teams is central to shaping long-term infrastructure and compute strategy.
This role involves managing and negotiating complex commercial and procurement contracts for Anthropic's EMEA operations, with a focus on supporting AI technology transactions. The Contracts Manager will work closely with legal and business teams to streamline contract processes, implement scalable solutions, and align regional execution with global legal strategy. Key responsibilities include drafting agreements, improving contracting efficiency, and enabling cross-functional stakeholders through local rollout of policies and initiatives.
Lead a London-based engineering team building critical connectivity infrastructure for AI agents, including the MCP proxy, OAuth systems, and token management. Drive reliability, security, and scalability across distributed systems used in enterprise environments. Collaborate closely with San Francisco teams to shape the future of agent tool integration and contribute to open standards.
