Principal Engineer, Privacy

Overview

Principal Engineer, Privacy at Anthropic. Set technical strategy for how personal data is handled across products, research and infrastructure, and lead the hardest privacy engineering work, influencing through quality of thinking and trust rather than formal authority.

What you'll do

• Define and drive technical strategy and architecture for major areas of privacy, spanning product surfaces, research and training data, internal tooling, and multiple clouds.
• Identify and lead the highest-complexity, company-critical privacy initiatives, guiding engineers across many teams.
• Be comfortable building the most difficult pieces yourself.
• Architect the primitives that make privacy the default and the safe path the fastest one: data discovery, classification, lineage, purpose-based access control, audit, retention, deletion, and export.
• Turn regulatory, contractual, and consent obligations (e.g., GDPR, CCPA, HIPAA, the EU AI Act) into enforced, continuously verified technical controls in partnership with Legal, Policy, and Compliance.
• Anticipate where AI capabilities, regulation, and customer expectations are heading, and position our systems ahead of them.
• Mentor and develop staff and senior staff engineers, raise the bar for privacy design across engineering, and help hire senior privacy talent.
• Represent Anthropic's privacy engineering to customers, regulators, standards bodies, and the research community.

What you'll need

• A track record of operating as a Principal engineer or equivalent: setting technical direction that multiple teams adopted, and delivering company-critical, multi-year initiatives.
• Deep experience applying privacy engineering principles in production systems with a large user base, including privacy by design, data minimization, and purpose limitation.
• Experience architecting data governance infrastructure (classification, lineage, access control, retention, or deletion) across distributed systems and cloud infrastructure at scale.
• Proficiency in Python, Go, or similar languages; effective at writing design docs, making architectural calls, and coding in critical paths.
• Understanding of privacy regulations such as GDPR and CCPA, and the ability to work as a peer with legal and policy experts to turn requirements into technical designs.
• Written and verbal communication that builds alignment across engineering, research, legal, and product teams, up to senior leadership.
• Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience, in a field relevant to the role as demonstrated through coursework, training, or professional experience.

Nice to have

• Experience building privacy infrastructure or controls for machine learning or AI systems, including training data governance or AI agents.
• Hands-on experience with privacy-enhancing technologies (e.g., differential privacy, homomorphic encryption, secure enclaves, secure multi-party computation).
• Experience establishing or re-architecting a privacy engineering practice under enterprise-customer or regulatory scrutiny.
• Experience briefing executives, auditors, regulators, or enterprise customers on privacy risk, and defending your recommendations under challenge.
• A history of growing engineers into Staff-level and more senior roles.
• Contributions to open-source privacy tooling, privacy research, or industry standards.

Details

• Locations: San Francisco, CA; Seattle, WA; New York City, NY. Remote-friendly with required travel.
• Location-based hybrid policy: staff are expected in one of the offices at least 25% of the time; some roles may require more.
• Annual salary: $485,000 – $625,000 USD.
• Visa sponsorship is available for some roles and candidates.
• For roles performing work in California, applicants with arrest or conviction records are considered in line with applicable fair chance laws.