Were looking for an Engineering Manager to build and lead our Privacy Engineering team:a small, high-leverage group responsible for designing and operating the privacy infrastructure that protects user data across our AI systems. Youll have an outsized impact in shaping how Anthropic builds world-class privacy into Claude from the ground up. This is a role with extraordinary scope and leverage. Youll own privacy engineering for Anthropic end-to-end.The work that spans privacy-preserving architectures for AI training and inference, foundational data governance and lifecycle systems, and the automated controls that turn complex regulation into engineering reality. Youll lead a team of talented privacy engineers that builds and operates the platform and infra frameworks underpinning Anthropics privacy and compliance posture. Your job is to scale the team and its charter as Anthropic grows. . Working at the intersection of privacy engineering, AI safety, and distributed systems, your team will solve novel challenges in protecting user data at scale, handling billions of conversations while maintaining model quality and research velocity. If owning the whole problem and having an outsized impact on how a frontier AI lab protects its users sounds compelling, this role might be for you. Key Responsibilities • Build and lead the team: Recruit, develop, and retain a team of exceptional privacy engineers; establish team charter, practices, and priorities as the team matures • Drive technical strategy: Partner with technical leads, researchers, and legal to set direction for privacy infrastructure across training, inference, and product surfaces: data governance and policy enforcement, deletion and retention at scale, encryption and key management, audit and access transparency, and ML-based PII detection and redaction. • Build foundational privacy infrastructure: Guide the team in building automated data discovery, classification, access controls, audit logging, and lifecycle management systems, plus data governance platforms for tracking lineage, purpose limitation, and retention across distributed AI systems • Translate regulation into engineering: Ensure the team turns complex regulatory requirements (GDPR, CCPA, HIPAA, EU AI Act) into actionable technical implementations and automated compliance controls • Lead privacy reviews at scale: Oversee technical privacy reviews and threat modeling for new AI models and features, identifying risks and architecting scalable mitigations • Enable privacy by default: Champion privacy engineering toolkits and frameworks that let all engineers build privacy-preserving features by default, and embed privacy controls into Claudes inference systems, interfaces, and data pipelines • Communicate and coordinate: Work closely with security, legal, data infrastructure, research, and go-to-market teams; clearly articulate dependencies, risks, and progress to stakeholders, and advocate for privacy as central to our mission of AI safety. • Stay technically grounded: Maintain enough technical depth to understand your teams work, provide meaningful guidance, and credibly represent privacy concerns in cross-functional discussions About You Were looking for a technical leader who thinks of themselves as a problem-solver and team-builder first. The ideal candidate has: Required: • Significant experience managing engineering teams, including hiring and growing teams through periods of ambiguity and rapid change • Deep expertise in privacy engineering principles: privacy by design, data minimization, and purpose limitation • Strong technical foundation in data governance and privacy infrastructure (policy enforcement, deletion/retention/lineage systems, encryption key management, audit logging) and the ability to discuss them at a level that earns respect from senior ICs. • Strong understanding of privacy regulations (GDPR, CCPA) and the ability to translate legal requirements into technical solutions • Experience with data governance, classification, and lifecycle management systems serving large user bases • Ability to balance technical depth with pragmatic decision-making; you know when to dive deep and when to trust your team • Strong communication skills: you can translate complex privacy challenges into business terms and vice versa • Comfort with end-to-end ownership, including defining practices where industry precedent is thin Preferred: • 8+ years of experience managing technical teams • Experience growing an engineering team and charter through a period of rapid company scaling. • Experience conducting privacy reviews, threat modeling, and risk assessments for production systems • Proven track record of designing and implementing privacy infrastructure serving millions of users • Experience at companies during periods of hypergrowth where youve scaled privacy alongside the business • Exposure to AI/ML infrastructure and the unique privacy demands of large-scale training and inference The annual compensation range for this role is listed below. For sales roles, the range provided is the roles 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: $405,000-$485,000 USD Logistics Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we arent able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if youre interested in this work. We think AI systems like the ones were building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.