Staff Software Engineer (Code RL)

Join Anthropic, a leading AI safety and research company, as a Staff Software Engineer. In this role, you will drive reinforcement learning efforts behind Claude's coding capabilities, create and scale agentic coding environments, and solve the engineering side of research efforts. You will have the opportunity to set technical direction and standards, work directly in research codebases, and contribute to the reliability of production RL systems. This position offers a competitive salary, comprehensive benefits, and the chance to make a significant impact in the field of AI.

• Design and implement widely-used APIs, frameworks, and abstractions that other engineers and researchers build on, with careful attention to interface legibility and principled defaults.
• Embed with research teams on a rotational basis to understand their engineering needs, build systems and APIs that support their work, and transfer ownership so teams can maintain those systems after you rotate off.
• Contribute to the reliability of production reinforcement learning systems, including monitoring, regression detection, and triage tooling.
• Familiarity with reinforcement learning concepts, agentic systems, or LLM training pipelines
• A track record of designing intuitive, safe APIs or frameworks that other engineers or teams adopted and built on
• Experience building or operating large-scale distributed systems
• Prior experience maintaining an open source project
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms
• Experience defining code standards, lint rules, or static verification approaches adopted across multiple teams
• Strong written and verbal communication skills, including the ability to explain system designs to collaborators with varied engineering backgrounds
• Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant Python code
• Experience designing plugin systems or extensible class hierarchies used across an organization
• Prior experience as a technical lead, or setting engineering standards for a team
• Experience working productively in large, evolving, or research-style codebases that you didn't originally write
• Demonstrated ability to anticipate failure modes — especially silent ones — and prevent them structurally through system design, type safety, and testing
• Comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Experience with large-scale data processing or dataset lifecycle management
• Experience embedding with or consulting for other teams, including successfully handing off systems for others to own
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows
• We encourage you to apply even if you do not believe you meet every single qualification