Product Manager, Public Sector

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.

Governments do some of the most consequential work there is: deciding benefits claims, getting veterans to care, investigating financial misconduct, running unemployment insurance, and producing the analysis that world leaders act on. Anthropic's public sector team exists to put Claude in the production path of that work. In the US and some allied governments, Claude is already in daily use across major agencies and US states.

The next steps need a particular kind of product manager: someone who can walk into an institution they have never worked with, sit with the people doing the work and find, alongside them, the workflow that matters. The best government products we know of started as an idea that came out of the room rather than a requirements document.

The scope is large: a product portfolio here is a set of governments rather than a feature area. A year in, success looks like agencies delivering services more effectively because public servants are doing core parts of their job with Claude in the loop, and at least one thing that you learn from them shipping to every Anthropic enterprise. That is a lot of surface; you will have to choose where to go deep, and we will back the choice.

We are hiring across civilian, state and local, govtech, and national security portfolios and will match you to one on background and interest. Some portfolios require eligibility for a US security clearance, though most do not. You would be among the first product managers on the team, working with a dedicated engineering and research team and with the policy, go-to-market, customer success, and applied AI leads who already spend their days inside these agencies.

• Alongside GTM, run discovery inside government institutions to find where Claude belongs in the production path of their work, then shape the product around what you find
• Own product decisions for our government models and product offerings and the agency workflows built on top of them
• Spot the government needs worth generalizing and carry them into Anthropic's broader roadmap. Many of Anthropic’s commercial features started as public-sector customer problems
• Help Anthropic navigate government compliance regimes
• Partner with our cloud and integration partners

• Have shipped successful products end-to-end. We weigh product judgment above any domain credential
• Can point to something you built that was your idea: it came from watching people work rather than from a requirements document
• Get things done through teams that don't report to you. In addition to the dedicated team, this role runs through a variety of partner teams inside Anthropic and many offices inside each agency.
• Move on your own clock. You have shipped in an organization with a fast cadence, or you set the pace in an environment that didn't
• Have built domain intuition fast in large enterprises that do not resemble each other

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.

• Roughly 7+ years building and shipping products, or equivalent scope
• Real intuition for how government operates, earned either from the inside or at a digital services organization or by building products public servants actually use
• Taken a public-sector or field requirement into a commercial product that succeeded
• Fluency with AI products: evaluations, model behavior as part of the product surface

$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.