Engineering Manager, Data Architecture (AI)

TL;DR

Engineering Manager, Data Architecture (AI): Leading the team responsible for building a world-class data infrastructure platform to support AI safety and regulatory compliance with an accent on scalability, security, and PII management. Focus on designing petabyte-scale data pipelines, implementing robust governance, and ensuring multi-cloud data reliability.

Location: Hybrid (San Francisco, CA or Seattle, WA). Staff are expected in the office at least 25% of the time.

Salary: $405,000 - $485,000 USD

Company

Anthropic is a public benefit corporation dedicated to creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

• Recruit and mentor a team of world-class data and infrastructure engineers, establishing technical vision and operational standards.
• Define the long-term architecture for the data stack to support high-velocity model training and complex inference workloads.
• Lead the design and implementation of automated, petabyte-scale data pipelines with high reliability and performance.
• Build systems for automated data discovery, lineage tracking, and lifecycle management to ensure data integrity.
• Ensure data architecture supports global privacy regulations and security through automated controls and privacy-preserving architectures.
• Partner with ML, Product, and Legal teams to unlock data utility without compromising AI safety.

Requirements

• Extensive experience managing and scaling engineering teams in high-growth environments, specifically within data infrastructure or distributed systems.
• Deep technical expertise in data modeling, database internals, and large-scale warehouse/lakehouse architectures.
• Proven track record of architecting cloud-native, scalable data platforms for multi-cloud deployments.
• Strong foundation in data governance, including metadata management and automated quality enforcement.
• Ability to translate broad business goals into actionable technical roadmaps in high-ambiguity environments.
• Must be based in or able to work from San Francisco, CA or Seattle, WA.

Nice to have

• 8+ years of experience managing technical teams.
• Experience scaling privacy infrastructure for millions of users during periods of hypergrowth.
• Exposure to AI/ML infrastructure and the unique privacy demands of large-scale training and inference.
• Experience conducting privacy reviews, threat modeling, and risk assessments for production systems.

Culture & Benefits

• Competitive compensation and optional equity donation matching.
• Generous vacation and parental leave with flexible working hours.
• Collaborative "big science" environment focused on high-impact, long-term AI safety goals.
• Visa sponsorship is available for qualified candidates.