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Salary: USD 320,000 - 405,000 / annual
Anthropic is hiring a Security Engineer to work on reinforcement learning (RL) infrastructure security. Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system with training, sampling, and environment execution running concurrently across a large fleet of accelerators and hosts. Your role is to keep that system secure as it scales.
This is a hands-on engineering position working directly in the RL codebase and the infrastructure underneath it, alongside the engineers and researchers who build and use it. The system is large and changes rapidly as research evolves, so security work must keep pace without sacrificing performance or velocity.
Anthropicis hiring from two backgrounds: security engineers interested in large-scale ML systems, and ML systems or research engineers interested in security. Strong candidates have depth in one area and genuine interest in the other.
Key responsibilities include:
- Design, build, and operate security controls for RL training systems and their infrastructure
- Work across the full stack (orchestration, environments, training, inference) wherever needed
- Review designs and code across the RL stack to identify and fix security problems
- Build shared libraries and tooling that other RL engineers and researchers depend on
- Develop observability to understand what these systems are doing
- Collaborate with researchers and performance engineers to ensure security changes preserve training correctness and performance
- Write clear design documents for your work
Anthropicis a public benefit corporation headquartered in San Francisco, focused on creating reliable, interpretable, and steerable AI systems. The company offers competitive compensation, optional equity donation matching, generous vacation and parental leave, flexible working hours, and collaborative office space. Currently, all staff are expected to be in one of the offices at least 25% of the time, though some roles may require more time on-site. Visa sponsorship is available.
REQUIREMENTS:
Minimum qualifications:
- Strong software engineering skills in Python and at least one systems language (Rust, C++, or Go)
- Experience designing, building, and operating large-scale distributed systems or security systems in production
- Strong understanding of security fundamentals
- Working knowledge of Linux, containers, and cloud infrastructure
- Experience debugging complex problems across many hosts and services
- Ability to reason about tradeoffs between security, performance, and reliability
- Strong written communication skills, including design documents
- Bachelor's degree or equivalent combination of education, training, and professional experience in a field relevant to the role
Preferred qualifications:
- Experience running ML training or inference infrastructure at scale
- Experience with infrastructure security (isolation, access control, networking, identity)
- Experience with container orchestration (Kubernetes) and sandboxed or virtualized code execution at scale
- Experience building observability for large fleets
- Experience supporting research teams or other fast-moving internal users
- Familiarity with reinforcement learning or large language model training workloads
