25 days ago
Base Salary
$405k - $605k/yr
Responsibilities
- Design widely used APIs, frameworks, and abstractions that make correct usage the default and prevent classes of errors structurally.
- Own the platform layers beneath every environment, including the agent runtime.
- Build production tooling that enables environment owners to understand, debug, maintain, and repair their environments independently.
- Embed with research teams, contribute directly to their codebases, and transfer system ownership when rotating off.
- Prevent silent failures through type safety, invariants, targeted testing, and correctness-focused refactoring.
- Drive organization-wide adoption of new frameworks, including deprecations and cutovers.
- Help define engineering standards, review practices, and design patterns for a new team.
- Mentor researchers and engineers in adopting frameworks and engineering practices.
Requirements
- Deep expertise in Python, including static typing, safe asynchronous and concurrency patterns, and performant code.
- Strong API and framework design skills with a track record of adoption by engineers or teams.
- Experience designing or operating stateful concurrent or distributed systems and reasoning about failure, retries, idempotency, and consistency.
- Experience working productively in large, evolving, or research-style codebases that the candidate did not originally write.
- Strong written and verbal communication skills and the ability to scope and drive ambiguous work to a maintainable outcome.
- Bachelor’s degree in a relevant field or an equivalent combination of education, training, and/or experience.
- Preferred: experience with infrastructure, tooling, or frameworks for machine-learning research or reinforcement-learning workflows.
- Preferred: experience with agent frameworks, orchestration engines, multi-agent systems, checkpoint and restore, replay, and long-running stateful processes.
- Preferred: experience using AI coding tools where correctness matters and results require verification.
- Preferred: experience with client libraries or SDKs for sandboxed, containerized, or remote execution platforms.
- Preferred: experience with large-scale data processing, dataset lifecycle management, or data lineage systems.
- Preferred: experience designing serialization schemes, plugin systems, or extensible class hierarchies.
- Preferred: experience embedding with or consulting for other teams, defining organization-wide code standards, or serving as a technical lead.
Benefits
- Hybrid policy requiring staff to work in an office at least 25% of the time
- Visa sponsorship with immigration-lawyer support
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Office space for collaboration
About Anthropic
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.