Security Engineer / Research Engineer, RL Security

Anthropic's mission is to create reliable, interpretable, and steerable AI systems.

As a Security Engineer / Research Engineer in RL Security, you will work on keeping the reinforcement learning system secure as it scales.

Key Responsibilities:

• Design, build, and operate security controls for RL training systems and infrastructure
• Work across the stack (orchestration, environments, training, inference) as needed
• Review designs and code, find security problems, and fix them
• Build shared libraries and tooling for other RL engineers and researchers
• Develop observability to understand system behavior
• Collaborate with researchers and performance engineers to preserve training correctness and performance
• Write clear design documents

Minimum Qualifications:

• Strong software engineering skills in Python and a systems language (Rust, C++, or Go)
• Experience with large-scale distributed systems or security systems in production
• Understanding of security fundamentals
• Working knowledge of Linux, containers, and cloud infrastructure
• Experience debugging complex problems
• Ability to reason about tradeoffs between security, performance, and reliability
• Strong written communication

Preferred Qualifications:

• Experience with ML training or inference infrastructure at scale
• Infrastructure security experience (isolation, access control, networking, identity)
• Container orchestration (Kubernetes) and sandboxed code execution
• Building observability for large fleets
• Supporting research teams or fast-moving internal users
• Familiarity with reinforcement learning or large language model training

The annual compensation range for this role is $320,000-$405,000 USD.