Product Manager, AI Enablement
Own the product experience that turns AI capabilities into measurable, repeatable workflows for internal business teams. The role requires 3+ years of product or related experience, hands-on agentic system development, strong process-mapping skills, and the ability to measure adoption and ROI.
About the job
Responsibilities
- Map current-state workflows end to end with stakeholders, identifying tools, context, and opportunities for AI-enabled efficiency.
- Build and manage a portfolio of internal AI tools, agentic workflows, and prompt-based copilots, taking projects from prototype through production.
- Audit AI features in existing enterprise tools before creating new solutions.
- Extend shared AI platforms and agent infrastructure to support new use cases.
- Design and implement the process for moving AI concepts from prototype to production, including evaluation, human-in-the-loop review, rollout criteria, and post-launch monitoring.
- Consolidate reusable learnings, tooling, and documentation across Finance, RevOps, People, Recruiting, Customer Success, Marketing, and Legal.
- Define success metrics, measure usage and adoption, and communicate ROI for AI investments.
- Drive adoption through workshops, onboarding, office hours, coaching, and practical guardrails.
- Travel approximately six times per year for team off-sites, workshops, and company events.
Requirements
- 3+ years of experience in product management, product operations, AI enablement, or a closely related role at a technology company.
- Demonstrated PM-level ownership of scope, requirements, delivery, and metrics.
- Strong process-mapping skills and the ability to use workflow maps as the foundation for AI solutions.
- Hands-on experience with frontier AI command-line interfaces and coding tools, including Codex, Claude Code, Anti-Gravity, and/or SuperGrok.
- Demonstrated ability to build and ship agentic systems that solve discrete, measurable problems.
- GitHub or equivalent portfolio showing approximately 3–4 built projects, or the ability to explain shipped work in detail.
- Fluency in context engineering and ontology design.
- Conceptual understanding of test-driven development and eval-driven development for AI systems.
- Ability to define success metrics, track adoption, and make the ROI case to skeptical stakeholders.
Nice-to-haves
- Experience with meta harnesses and multi-agent orchestration frameworks.
- Familiarity with retrieval-augmented generation (RAG), LLM output evaluation, hallucination mitigation, and enterprise release gating.
- Exposure to AI acceptable-use policies, data-handling guardrails, or workforce governance frameworks.
- Experience in high-growth, AI-native, or B2B SaaS environments.
- Experience creating enablement content, use-case libraries, or office-hours programs from scratch.
Skills
Product Management, Process Mapping, Ai Enablement, Codex, Claude Code, Agentic Systems, Context Engineering, Ontology Design, Test-Driven Development, Eval-Driven Development, Multi-Agent Orchestration, RAG, Llm Evaluation, Hallucination Mitigation, GitHub
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