Software Engineer, Sandboxing

Anthropic Anthropic · AI Frontier · San Francisco, CA · AI Research & Engineering

Software Engineer to contribute to Anthropic's sandboxing infrastructure, which enables Claude to safely execute code and interact with external systems. The role focuses on the client-side library/API and underlying infrastructure, emphasizing reliability, security, and developer experience.

What you'd actually do

  1. Contribute to the client library, API surface, and underlying infrastructure for Anthropic's sandboxing system, ensuring it is reliable, well-documented, and intuitive to use
  2. Drive down error rates and improve correctness through systematic debugging, monitoring, and proactive fixes
  3. Help develop and maintain a product roadmap for sandboxing capabilities, balancing immediate needs with long-term architectural improvements
  4. Partner closely with internal teams using the sandboxing system to understand their requirements, debug issues, and build tooling that serves their use cases
  5. Respond to incidents and production issues with urgency, conducting thorough root cause analysis and implementing preventive measures

Skills

Required

  • 5+ years of software engineering experience
  • maintaining libraries, SDKs, or developer-facing APIs
  • operating complex distributed systems
  • systematically improving reliability
  • developing and articulating a long-term vision for a product
  • comfortable with ambiguity
  • context-switch between reactive incident work and proactive product development
  • communicate clearly with both technical and non-technical stakeholders

Nice to have

  • founder or early engineer at an infrastructure-focused startup
  • security, sandboxing, or isolation technologies (containers, VMs, seccomp, namespaces, etc.)
  • Open-source contributions in the Python ecosystem
  • building developer tools, CLIs, or platforms used by other engineers
  • working on incident response and on-call rotations for production systems
  • Exposure to reinforcement learning or model training infrastructure

What the JD emphasized

  • 5+ years of software engineering experience
  • track record of systematically improving reliability