Anthropic
Staff+ Software Engineer, Safeguards Data
$320K–$485K
New York City, NY +1 · Staff · Full-time · Posted Aug 14, 2026
- Location
- New York City, NY
New York, New York, United States - Experience
- Preferred: 8+ years as a software engineer. Minimum years correlate with internal job-level requirements.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; required field of study is relevant to the role, as demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; if an offer is made, Anthropic will make every reasonable effort to obtain a visa and provides an immigration lawyer.
About the job
Builds and operates privacy-safe data infrastructure for Safeguards, enabling detection, evaluation, investigation, and review systems to use sensitive data securely and reliably.
What you'll do
- Design and operate data stores, pipelines, schemas, and APIs for Safeguards systems.
- Build privacy-safe interfaces and scale distributed storage, ingestion, and processing across deployment environments.
- Collaborate across teams on safe data use, lead technical design and architectural reviews, and participate in on-call and incident reviews.
What they ask for
- Strong systems fundamentals and experience building and operating large-scale, fault-tolerant distributed systems.
- Experience operating systems handling sensitive or high-value data with access, privacy, retention, and security controls designed in.
- Track record building platforms or internal tools widely adopted by other teams.
- Led technical design of projects spanning several engineers or teams.
Nice to have
- Proficiency in a systems language such as C, C++, Rust, or Go.
- Experience with ML data infrastructure, data governance in regulated or high-sensitivity domains, or agentic coding tools such as Claude Code.
Pay
$320,000 — $485,000 USD (base salary)
Tools
AWS, GCP, Azure, C, C++, Rust, Go, Claude Code
AI focus
Enables ML training, evaluation, and investigation workflows to use sensitive data safely; supports safeguards systems for AI safety.
Model-written summary · the original posting is authoritative