About the job
About Anthropic
Anthropic is committed to building AI systems that are reliable, interpretable, and steerable. The team’s mission centers on making AI safe and beneficial for both users and society. Researchers, engineers, policy experts, and business leaders collaborate closely to advance this goal as the company grows.
Role Overview: Infrastructure Engineer (Sandboxing Team)
The Infrastructure Engineer will join the Sandboxing team within Anthropic’s Research organization in Berlin. This role focuses on designing and scaling the systems that let researchers safely run and experiment with AI-generated code and interactions inside controlled environments.
As Anthropic’s AI models become more capable, secure execution infrastructure grows in importance. The work involves building distributed systems that must operate reliably at scale while maintaining strict security boundaries. Contributions in this position directly support Anthropic’s mission to develop safe, beneficial, and trustworthy AI systems.
Key Responsibilities
- Design, build, and maintain distributed backend systems for secure sandboxed execution environments.
- Scale infrastructure to support expanding research and product needs, focusing on reliability and performance.
- Implement and manage serverless architectures and container orchestration systems.
- Collaborate with research teams to gather requirements and translate them into effective infrastructure solutions.
- Develop monitoring, alerting, and observability systems to ensure high operational standards.
- Participate in on-call rotations and incident response to help maintain system reliability.
- Enhance infrastructure automation and tooling to improve developer productivity.
- Work with security teams to ensure sandboxing infrastructure meets required isolation standards.
What Makes a Strong Candidate
- More than 5 years of experience building and managing backend infrastructure at scale.
- Deep understanding of distributed systems design and implementation.
- Strong operational background, including troubleshooting complex production issues.
- Proficiency with cloud platforms, especially GCP/GCS; experience with AWS or Azure is a plus.
- Familiarity with containerization technologies and practices.
