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AI Product Manager, Public Sector

Washington, DC or San Francisco, CA; OnsiteOnsite · United States
Defense Tech
POSTED 2 SEPT
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Role
68 days opentrue age
Posted 2 Sept
Payin text
$147k–185kposted
▲ +127% vs market median $73k
$34k$185k
Market p25–p75
$34k–$135k
Washington DC · n=18 · 365d to 6 Nov
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All tracked boards · live 9 Nov · n=3,988

AI Product Manager, Public Sector

Compensation: $147,000 – $185,000 base salary, plus equity, company benefits, and incentive compensation.

Location: Washington, DC or San Francisco, CA. These are the only two locations under consideration. No other locations, and no fully remote option.

Role Type: Full-Time Employee, Individual Contributor

Work Model: Customer-facing product role, with regular on-site engagement and travel as needed

Clearance: U.S. Citizenship required; active clearance preferred, eligibility and willingness to obtain one required

Client name withheld. Sitreps Talent is managing the search, and interested candidates apply through Sitreps.

About the Client

Our client is a venture-backed AI security company. Their platform helps government and enterprise customers put AI systems into production safely: evaluating models and applications before deployment, protecting sensitive data and enforcing policy at runtime, governing what AI agents are allowed to do, and maintaining the evidence trail oversight bodies require. The platform runs across cloud, hybrid, on-prem, edge, and air-gapped environments. The team is standing up a dedicated public sector organization, and these are early seats on it.

About the Role

Our client is looking for a Public Sector AI Product Manager to help shape their platform for high-consequence government and national security environments.

This role sits at the intersection of AI product strategy, customer discovery, technical execution, public sector mission needs, and go-to-market enablement. You will work directly with government stakeholders, mission users, technical evaluators, security teams, and the company's engineering, research, delivery, and growth teams to turn customer signal into product direction.

This is a hands-on, customer-facing product role. You will define product requirements, guide roadmap priorities, support pilots and deployments, analyze model and system behavior, and make sure investment translates into measurable customer and mission outcomes.

Responsibilities

  • Become deeply fluent in the company's evaluation, guardrail, and agent governance platform.
  • Build deep relationships with public sector customers, mission users, technical evaluators, and executive stakeholders to understand operational needs, constraints, and success criteria.
  • Translate customer signal into product strategy, business cases, roadmap priorities, PRDs, and measurable product requirements.
  • Lead discovery, prototyping, and iteration for public sector use cases across AI evaluation, red-teaming, runtime controls, governance, observability, and agentic systems.
  • Partner with engineering, research, design, delivery, and go-to-market teams to prioritize and ship capabilities that solve real customer problems.
  • Analyze AI system behavior, evaluation results, datasets, failure modes, guardrail decisions, and customer workflows to refine product direction.
  • Create customer-facing narratives, demos, product collateral, battle cards, and executive-ready materials that support adoption and market readiness.
  • Track whether product investments are delivering measurable outcomes, including risk reduction, deployment acceleration, operational control, and mission value.

You Might Thrive in This Role If You

  • Enjoy operating at the intersection of AI, product strategy, mission needs, technical execution, and customer outcomes.
  • Have strong ownership instincts and are comfortable driving product direction through ambiguity.
  • Communicate clearly with engineers, researchers, executives, technical evaluators, mission users, and go-to-market teams.
  • Like spending time with customers directly, including on-site, to build a high-fidelity understanding of their workflows and constraints.
  • Are comfortable turning messy feedback, prototype learnings, and field observations into clear product decisions.
  • Think in terms of measurable outcomes, not just shipped features.
  • Are excited to shape AI evaluation, runtime control, and agent governance products for high-stakes public sector environments.
Source · SitrepsFirst seen 2 NovOriginal ↗