Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Security @ 3
Communication @ 6
API @ 3
Engineering Management @ 5
Compliance @ 3
AI @ 3
Data Pipelines @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
The Safeguards Data Infrastructure team owns the offline data stack that underpins our safeguards work: the storage layer for sensitive user data, the tooling built on top of it, and the interfaces that let the rest of the Safeguards organization access that data safely and ergonomically. As Engineering Manager of this team, you'll be responsible for ensuring portability of the safeguards data stack across deployment environments, building privacy-preserving data interfaces that enable ML and training workflows, and driving compliance with data regulations including HIPAA.
Responsibilities
- Lead and grow a team of engineers delivering the data infrastructure and tooling that powers Anthropic's safeguards capabilities.
- Own strategy and execution for porting the safeguards offline data stack (including PII storage and tooling) across new cloud and deployment environments.
- Build and maintain privacy-safe data APIs and interfaces that enable ML and training workflows while respecting data retention and access constraints.
- Drive tooling and architecture decisions to maximize data retention within privacy and compliance requirements.
- Manage privacy incident response processes and partner with compliance teams on regulatory requirements (e.g., HIPAA, EU privacy regulations).
- Collaborate closely with enterprise customers and product teams on zero data retention offerings and enterprise data contracts.
- Independently own and drive multiple workstreams, including planning, execution, and cross-team coordination.
- Coach, mentor, and support career development of direct reports; partner with recruiting to attract, hire, and retain engineering talent.
Requirements
- 4+ years of front-line engineering management experience.
- Track record of leading teams that build and operate data infrastructure at scale.
- Hands-on software engineering experience as an individual contributor prior to moving into management.
- Strong understanding of data privacy principles, PII handling, and compliance frameworks.
- Comfortable driving technical decisions in ambiguous, fast-moving environments with competing priorities.
- Experience working cross-functionally across infrastructure, product, and compliance or security teams.
- Clear and persuasive communicator, both in writing and in person.
Strong candidates may also
- Experience with multi-cloud or multi-region data portability, particularly in regulated environments.
- Built privacy-preserving data pipelines or interfaces for ML workloads.
- Experience with enterprise data contracts or zero data retention architectures.
- Explored novel approaches to data processing under strict access constraints (e.g., in-memory storage and compute for sensitive data).
- Passion for building diverse and inclusive teams.
Compensation
- Annual Salary (USD): $405,000 - $485,000 USD
- Annual Salary (GBP): £325,000 - £390,000 GBP
Logistics
- Education requirements: At least a Bachelor's degree in a related field or equivalent experience.
- Location-based hybrid policy: staff are expected to be in one of our offices at least 25% of the time (some roles may require more).
- Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist, though sponsorship may not be successful for every role/candidate.
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Office space for collaboration
About Anthropic / How we're different
Anthropic is a public benefit corporation focusing on large-scale AI research as an empirical science. The company emphasizes collaboration, high-impact research directions, and strong communication skills. Anthropic is headquartered in San Francisco and values diverse perspectives across its teams.