
Staff + Software Security Engineer, Labs
About this role
Staff + Software Security Engineer, Labs is a full-time role at Anthropic based in San Francisco, CA, New York City, NY, or Seattle, WA. This position suits an ambitious generalist with deep technical expertise who wants to tackle high-risk security challenges for frontier artificial intelligence systems.
Role Overview
Anthropic is hiring a Staff + Software Security Engineer for its Security Labs team across San Francisco, New York City, and Seattle. The role involves running high-risk, rapid-iteration security projects focused on defending frontier artificial intelligence systems against advanced adversaries. Engineers on this team own projects end to end, testing unconventional security ideas, building prototypes, and either handing successful solutions over to production teams or documenting valuable lessons from failed bets.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Anthropic builds reliable, interpretable, and steerable artificial intelligence systems with the mission of ensuring AI remains safe and beneficial for users and society. The organization brings together committed researchers, engineers, policy experts, and business leaders to advance frontier artificial intelligence responsibly.
How to Apply
Candidates should apply directly on the official Anthropic careers page.
Skills and tech stack
Questions candidates ask
What locations are available for this role?
This role is available in San Francisco, CA, New York City, NY, or Seattle, WA.
What is the compensation range for this position?
The annual base salary ranges from $320,000 to $485,000 USD.
What kind of team is Security Labs at Anthropic?
Security Labs runs a portfolio of high-risk, high-expected-value security projects with short timelines, operating on weeks rather than quarters, where a meaningful fraction of bets are expected not to succeed.
What programming languages are required?
Candidates must be strong programmers in Python alongside at least one of Rust, Go, C, or C++.
Do I need machine learning infrastructure experience to apply?
Machine learning infrastructure experience is preferred rather than strictly required, though familiarity with training pipelines, distributed schedulers, inference serving, or accelerator hardware is helpful for conversing with researchers.