The opportunity
Anthropic's Environments organization builds and maintains the infrastructure that improves Claude’s capabilities through reinforcement learning. That includes the frameworks researchers use to build environments and the infrastructure responsible for running them.
What you'll do
Design widely used APIs, frameworks, and abstractions that other engineers: and researchers build on, making correct usage the default and ruling out entire classes of errors structurally
Own the platform layers that sit beneath every environment, including the agent runtime
Build the tooling that lets environment owners understand, debug, and: maintain their environments in production without needing an infrastructure engineer in the loop
Embed with research teams on a rotational basis, work directly in their: codebases without slowing down the research they support, and transfer ownership when you rotate off
Anticipate silent failure modes and prevent them structurally through type: safety, well-designed invariants, targeted testing, and refactors that reduce the room for correctness issues
Drive adoption of new frameworks across the organization, including deprecations and cutovers
What they're looking for
- Experience building infrastructure, tooling, or frameworks for machine: learning research or RL workflows, and familiarity with agentic systems or LLM training pipelines
- Experience building agent frameworks, orchestration engines, or multi-agent: systems, including checkpoint and restore, replay, and coordination of long-running stateful processes
- Experience using AI coding tools on code where correctness matters, with good: judgment about what to delegate and how to make the results verifiable
- Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms
- Experience with large-scale data processing, dataset lifecycle management, or data lineage systems
- Experience designing serialization schemes, plugin systems, or extensible: class hierarchies used across an organization
- Experience embedding with or consulting for other teams and handing off: systems for others to own, or defining code standards adopted across teams, or prior experience as a technical lead
