Engineering Manager - Privacy Infrastructure
$405,000–$485,000 year
On-site · San Francisco, California, United States
Job Summary
Lead privacy engineering for Anthropic by building and guiding a privacy infrastructure team that designs, operates, and scales privacy controls across AI training, inference, and product surfaces. Own data governance, policy enforcement, deletion/retention, encryption key management, audit logging, and ML-based PII detection/redaction. Translate GDPR/CCPA/HIPAA and other regulations into automated controls; drive threat modeling and privacy reviews for new models/features; champion privacy-by-default across Claude’s data pipelines and interfaces; collaborate with security, legal, data infrastructure, research, and GTM teams; communicate risks and progress to stakeholders; maintain technical depth to credibly represent privacy concerns in cross-functional discussions; support end-to-end ownership in a role requiring in-office presence in SF at least 25% of the time.
Required Qualifications
- 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)
- 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: translate complex privacy challenges into business terms and vice versa
- Comfort with end-to-end ownership, including defining practices where industry precedent is thin
- Strong leadership experience growing an engineering team and charter through rapid 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 you've 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 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.
- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
- Visa sponsorship: We sponsor visas; offer assistance to obtain visa where feasible
- Location-based hybrid policy: Office presence required at least 25% of the time
- Minimum years of experience: Years of experience correlated with internal job level requirements
- Minimum field of study: A field relevant to the role
- Not all strong candidates will meet every qualification as listed
Desired Qualifications
- Significant experience managing engineering teams
- Deep expertise in privacy engineering principles: privacy by design, data minimization, purpose limitation
- Strong technical foundation in data governance and privacy infrastructure (policy enforcement, deletion/retention/lineage systems, encryption key management, audit logging)
- Strong understanding of privacy regulations (GDPR, CCPA) and 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
- Strong communication skills to translate privacy challenges into business terms
- Comfort with end-to-end ownership, including defining practices where industry precedent is thin
- Experience growing an engineering team and charter through rapid 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 privacy scales with the business
- Exposure to AI/ML infrastructure and privacy demands of large-scale training/inference
- Experience sponsoring visas (H1B) is a plus
- Bachelor’s degree or equivalent combination of education, training, and/or experience
- Location-based hybrid policy requiring office presence at least 25% of time
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