485K–625K USD / year
Principal Engineer, Privacy
OtherHybrid — San Francisco, CA, Seattle, WA, New York City, NY
Published on 2026-11-10
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About this role
Set technical strategy and build privacy infrastructure across Anthropic’s products, research, training data, and cloud systems. Lead company-critical initiatives that make privacy controls enforceable by default, partnering across engineering, research, legal, policy, and compliance.
About the company
Anthropic builds reliable and interpretable AI systems, including the Claude family of models, for businesses and developers. The company focuses on AI safety research and practical AI assistants for enterprise and consumer use.
What you'll do
- Set privacy engineering strategy and architecture across products, research, training data, internal tooling, and cloud infrastructure
- Lead complex, company-critical privacy initiatives across teams and build critical components directly
- Architect data discovery, classification, lineage, access-control, auditing, retention, deletion, and export capabilities
- Translate regulatory, contractual, and consent requirements into continuously verified technical controls
- Mentor senior engineers, raise privacy design standards, and help hire senior privacy talent
- Represent privacy engineering with customers, regulators, standards bodies, and researchers
What we're looking for
- Principal-level experience setting technical direction across multiple teams and delivering company-critical initiatives
- Deep experience applying privacy engineering principles in large-scale production systems
- Experience architecting data governance infrastructure across distributed systems and cloud environments
- Proficiency in Python, Go, or similar languages, with strong design and coding skills
- Understanding of privacy regulations such as GDPR and CCPA, and experience translating requirements into technical designs
- Strong communication skills across engineering, research, legal, product, and senior leadership
Nice to have
- Privacy infrastructure experience for machine learning or AI systems, including training data governance or AI agents
- Hands-on experience with privacy-enhancing technologies such as differential privacy, homomorphic encryption, secure enclaves, or secure multi-party computation
- Experience establishing privacy engineering practices under enterprise or regulatory scrutiny
- Experience briefing executives, auditors, regulators, or enterprise customers on privacy risk
- History of developing engineers into Staff-level and more senior roles
- Contributions to open-source privacy tooling, privacy research, or industry standards
Benefits
- Generous vacation and parental leave
- Flexible working hours
- Optional equity donation matching
- Collaborative office space