Security Engineer / Research Engineer, RL Security

Location: San Francisco, CA; New York City, NY; or Seattle, WA. Hybrid policy: staff are expected to work from one of the offices at least 25% of the time, and some roles may require more office time.

Annual salary: $320,000–$405,000 USD.

Company

Anthropic builds reliable, interpretable, and steerable AI systems intended to be safe and beneficial for users and society.

What you will do

• Design, build, and operate security controls for reinforcement learning training systems and their infrastructure.
• Work across orchestration, environments, training, and inference systems.
• Review RL designs and code, identify security issues, and implement fixes.
• Build shared libraries, tooling, and observability for RL engineers and researchers.
• Collaborate with researchers and performance engineers to preserve training correctness and performance.
• Write clear design documents for implemented systems.

Requirements

• 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 production security systems.
• 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 documentation.
• Bachelor’s degree or an equivalent combination of education, training, and experience in a field relevant to the role, demonstrated through coursework, training, or professional experience.
• Years of experience required will correlate with the internal job-level requirements.

Nice to have

• Experience running ML training or inference infrastructure at scale.
• Experience with infrastructure security, including isolation, access control, networking, or identity.
• Experience with 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.

Culture & Benefits

• Collaborative research environment focused on large-scale AI research and trustworthy, steerable AI.
• Frequent research discussions and emphasis on clear communication.
• Flexible working hours and office-based collaboration.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.
• Visa sponsorship may be available, with immigration lawyer support, subject to role and candidate eligibility.

Hiring process

• Candidates may use AI during the application process according to Anthropic’s candidate AI usage policy.