Engineering Manager, Safeguards Data Infrastructure

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.

Anthropic's Safeguards team is responsible for the systems that allow us to deploy powerful AI models responsibly — and the data infrastructure underneath those systems is foundational to getting that right. 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 full portability of our safeguards data stack across an expanding set of deployment environments, building privacy-preserving data interfaces that enable ML and training workflows, and driving compliance with data regulations including HIPAA. This is a role at the intersection of infrastructure engineering, data privacy, and enterprise product requirements — and it sits at a critical juncture as Anthropic scales into new cloud environments and geographies.

• Lead and grow a team of engineers delivering the data infrastructure and tooling that powers Anthropic's safeguards capabilities
• Own the strategy and execution for porting the safeguards offline data stack — including PII storage and tooling — across new cloud and deployment environments as Anthropic expands
• 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 that maximize data retention within the bounds of our 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, working balancing safety needs with robust enterprise data contracts
• Independently own and drive multiple workstreams, including planning, execution, and cross-team coordination
• Coach, mentor, and support the career development of your direct reports, helping them set and achieve their professional goals
• Partner with recruiting to attract, hire, and retain strong engineering talent

• Have 3+ years of front-line engineering management experience
• Have hands-on software engineering experience as an individual contributor prior to moving into management
• Are comfortable driving technical decisions in an ambiguous, fast-moving environment with competing priorities
• Have experience working cross-functionally across infrastructure, product, and compliance or security teams
• Are clear and persuasive communicators, both in writing and in person

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.

• Have a track record of leading teams that build and operate data infrastructure at scale
• Have experience with multi-cloud or multi-region data portability, particularly in regulated environments
• Have built privacy-preserving data pipelines or interfaces for ML workloads
• Have experience with enterprise data contracts or zero data retention architectures

$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 aren't 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 you're interested in this work. We think AI systems like the ones we're 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.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.