Level

Anthropic

Product Manager, Enterprise Privacy

Anthropic is hiring a Product Manager, Enterprise Privacy in San Francisco and New York, United States. It pays $305k-$385k a year and Level rates it ; you can apply on Level.

AI in this role

ai-safetyai-research

About Anthropic

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.

About the role

As a Product Manager focused on Enterprise Privacy, you'll collaborate with Privacy Engineering, Infrastructure, Trust and Safety, Legal, Security, GTM, enterprise and platform product teams, and our cloud partners to evolve and extend the controls that enterprises, regulated industries, and governments require in order to bring their most sensitive work to Claude. You will synthesize complex and fast-changing business needs and partner closely with the teams that retain, protect, and govern customer data across Anthropic's first-party platform and Claude on AWS, GCP, and Azure. Together, you will ensure that privacy guarantees are enforced by our systems and are verifiable by our customers.

This is a high-visibility role with substantial scope. Anthropic offers layered controls over how customer data is retained and accessed, and you will build the product surface that lets customers understand, govern, and verify these controls. This includes retention and access controls, access logs and compliance reporting, customer-managed keys and custody, data residency, and self-serve user interfaces. Your stewardship of these privacy capabilities earns the customer trust that is essential to Anthropic's mission.

Key responsibilities

  • Deeply understand external customers with strict data handling requirements, from a bank's CISO to a healthcare system's compliance team to a government contractor's auditor, and the internal Trust and Safety, Legal, and GTM stakeholders whose needs pull in different directions.
  • Partner with Privacy Engineering to ship controls that unblock regulated customers, balance impact against engineering cost, and deliver at Anthropic speed.
  • Co-develop solutions with design-partner customers and their compliance teams, so shipped changes pass real audits, not just hypothetical ones.
  • Work with engineers to steer architecture and investment decisions with a long-term lens: balancing build versus buy versus rely-on-the-cloud-provider, and sequencing custody, residency, and transparency across clouds that ship on their own timelines.
  • Define success metrics for privacy controls, from preventing configuration incidents by design, to the speed at which customers can independently answer questions about their own data.
  • Define and iterate on the self-serve experience for compliance and security teams, expanding what an organization can check about its own posture, settings, and access history without having to wait on support tickets.
  • Gather and assess competing stakeholder needs and communicate prioritization trade-offs clearly to senior leadership, balancing privacy risk, safety requirements, legal exposure, and commercial impact. When something goes wrong, own what customers hear from us and when.
  • Work with engineering leads to decide how retention, access, residency, and custody controls are enforced, so that our infrastructure keeps the promises we make.

Minimum qualifications

  • Experience taking a new product area from ambiguity to a durable roadmap, and shipping controls that enterprises or regulators depend on.
  • A track record of driving platform capabilities that balance the needs of multiple customer segments and internal stakeholders.
  • The judgment to make prioritization trade-offs between customer demand, risk, and engineering cost, and the clarity to communicate them.
  • The ability to internalize how privacy, safety, legal risk, and commercial impact interact, and translate that understanding into a coherent product vision.
  • Experience building highly collaborative and effective relationships with engineers and key cross-functional stakeholders. You have equal credibility providing design doc feedback to engineers, negotiating a control with a CISO without losing the relationship, and explaining a risk trade-off to leadership.

Preferred qualifications

  • 8+ years of product management experience, with deep exposure to privacy, security, or compliance products.
  • Built or scaled audit logging, key management, data residency, retention, or access governance products for regulated customers.
  • Shipped controls across multiple cloud providers or partnered with AWS, GCP, or Azure at the platform level.
  • Worked with certification, attestation, or trust center programs (SOC 2, ISO 27001, FedRAMP).
  • Used Claude, Claude Code, or comparable agentic tools and formed opinions about the data controls they should offer.

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.

Annual Salary:$305,000—$385,000 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.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

How we rate this

Product Manager, Enterprise Privacy at Anthropic rates 67 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI SafetyAI Research

Questions you could be asked

  1. How do you think about the risk of an AI system in this kind of role failing silently?
  2. Tell me about a research question you investigated. What did you find?
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI Safety and AI Research. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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