Principal Engineer, Privacy
About the role
Anthropic is working on frontier AI systems that handle sensitive information at enormous scale. How we protect that data, and how we build privacy into our systems rather than bolting it on afterward, is central to our mission of building AI that is safe and beneficial.
As one of our principal privacy engineers, you will be among Anthropic's most senior individual contributors on privacy. You will set technical strategy for how personal data is handled across products, research, and infrastructure, and execute the hardest parts of delivering it. You'll work at the intersection of privacy engineering, distributed systems, and AI safety, on problems without established answers. You will lead through influence, quality of thinking, and trust rather than formal authority.
Key responsibilities
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 team
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
Minimum qualifications
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; you are effective 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
Preferred qualifications
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
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$485,000—$625,000 USD