AI Product Manager, Public Sector

Job description

### **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. ### **Requirements** ### **Preferred Qualifications** - 5+ years in product management, AI product strategy, technical program management, solutions, product engineering, strategy consulting, enterprise SaaS, or other customer-facing technical roles. - Deep expertise in Generative AI and LLM systems, including model behavior, evaluation design, red-teaming, RAG/copilot architectures, prompt injection, guardrails, observability, and agentic workflows. - Experience building, launching, or scaling technical products for enterprise, government, regulated, or mission-critical customers. - Strong technical fluency across AI/ML systems, APIs, cloud environments, cybersecurity, data infrastructure, or deployment architectures. - Ability to translate customer needs into product requirements, business cases, roadmap priorities, success metrics, and executive-ready narratives. - Strong analytical skills, including comfort working with datasets, benchmark results, evaluation outputs, user feedback, and product telemetry. - Excellent writing, presentation, prioritization, and cross-functional leadership skills. - Willingness to travel regularly to customer sites. - U.S. Citizenship required; active U.S. security clearance preferred, with eligibility and willingness to obtain one required. ### **Nice to Have** - Experience supporting Department of War, IC, federal civilian, or other public sector customers. - Familiarity with RMF, FedRAMP, IL environments, ATO processes, CMMC, or government software accreditation. - Experience with AI evaluation, red-teaming, runtime guardrails, model observability, AI governance, or agentic AI systems in production environments. - Familiarity with public sector acquisition pathways, including BAAs, OTAs, SBIR/STTR, IDIQs, production transition, or programs of record. - Experience partnering with systems integrators, primes, federal channel partners, or public sector resellers. - Prior experience at a defense-tech, AI, cybersecurity, cloud, or enterprise SaaS company. - Active Secret, Top Secret, or TS/SCI clearance.