Full-Stack Software Engineer in RL

Job title: Full-Stack Software Engineer in RL

About the Role As a Full-Stack Software Engineer in RL, you will build the platforms, tools, and interfaces that power environment creation, data collection, and training observability. You’ll own end-to-end product surfaces—from backend services and APIs to the web UIs used by researchers, external vendors, and thousands of data labelers.

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 ramp up in hours, not weeks
• Partner closely with RL researchers, data operations, and vendor management to translate ambiguous requirements into well-scoped, well-designed products

What We're Looking For

• Strong software engineering fundamentals and full-stack range — you're comfortable owning a surface from database schema to frontend
• Proficient in Python and a modern web stack (React, TypeScript, or similar)
• A track record of shipping systems that solved a hard problem, not just shipped on time — e.g. you built the thing that made your team 10x faster, or the internal tool nobody thought was possible
• Operate with high agency: you identify what needs to be done and drive it forward without waiting for a ticket
• Have found yourself wondering why this isn’t moving faster in previous roles — and then have done something about it
• Care about UX and can build interfaces that are intuitive for both technical researchers and non-technical labelers
• Communicate clearly with researchers, operations teams, and engineers, and can turn vague asks into well-scoped work
• Thrive in a fast-moving environment where Claude is your pair programmer, and the next problem is often one nobody has solved before
• Care about Anthropic's mission to build safe, beneficial AI and want your work to contribute directly to it

Nice to Have

• Built data collection, labeling, or annotation platforms — ideally ones that had to scale across many vendors or many task types
• Background building multi-tenant platforms with role-based access, audit trails, and vendor management workflows
• Experience with cloud infrastructure (GCP or AWS), Docker, and CI/CD pipelines
• Familiarity with LLM training, fine-tuning, or evaluation workflows
• Experience with async Python (Trio, asyncio) or high-throughput API design
• Background in dashboards, monitoring, or observability tooling
• Experience working directly with external vendors or partners on technical integrations
• A background that isn’t a straight line — e.g. math or physics into SWE, competitive programming, research into engineering, or a side project that outgrew its scope
• Representative projects include building a unified platform for human data collection and developing vendor onboarding automation that handles Docker registry access, API token management, and environment validation