Description
Anthropic's Environments organisation builds and maintains infrastructure that improves Claude's capabilities through reinforcement learning. You will design frameworks and APIs for researchers to build environments, run production RL, and maintain the infrastructure.
You will be a strong fit if you have deep expertise in Python, API and framework design experience, and intuition for complex system failures.
Key Responsibilities:
- Design widely used APIs, frameworks, and abstractions for engineers and researchers.
- Own platform layers beneath every environment, including the agent runtime.
- Build tooling for environment owners to understand, debug, and maintain their environments.
- Embed with research teams, work directly in their codebases, and transfer ownership.
- Anticipate and prevent silent failure modes through type safety, testing, and refactors.
- Drive adoption of new frameworks and define engineering standards.
Minimum Qualifications:
- Deep expertise in Python, static typing, and performance.
- Strong taste in API and framework design.
- Experience with stateful concurrent or distributed systems.
- Verification mindset with measurement and checks.
- Experience in large, evolving codebases.
- Strong written and verbal communication.
Preferred Qualifications:
- Experience with machine learning research or RL workflows.
- Building agent frameworks, orchestration engines, or multi-agent systems.
- Using AI coding tools for verifiable code.
- Client libraries or SDKs on sandboxed platforms.
- Large-scale data processing or dataset lifecycle management.
The annual compensation range for this role is $405,000-$605,000 USD.