Director, AI Platform Product Management

What you'll do

• Own the end-to-end product lifecycle for an enterprise AI platform, including strategy, roadmap, and adoption outcomes.
• Define product boundaries, gating requirements, and evidence standards for a greenfield platform where no precedent exists.
• Translate complex AI governance, risk, privacy, and security requirements into functional product capabilities and user workflows.
• Conduct customer discovery to convert research and feedback into clear product opportunities for teams building AI agents.
• Prioritize initiatives based on value, feasibility, and impact while managing trade-offs across scope and timing.
• Establish performance indicators to measure platform adoption and demonstrate measurable business and operational impact.
• Partner with engineering, legal, and compliance teams to ensure solutions are scalable and meet regulatory requirements.
• Communicate product direction, rationale, and progress to stakeholders across a global enterprise environment.

What we're looking for

• Bachelor's degree and 8+ years of product management experience (or 7+ with MBA/MS, 5+ with PhD/JD, or 4+ with MD/DVM).
• Demonstrated end-to-end product accountability covering strategy, roadmap, and adoption outcomes.
• Experience with AI-enabled or agentic products, including platforms for teams that build and operate AI agents.
• Working fluency in technical foundations of modern AI products, including agent tooling, model evaluation, and cost measurement.
• Experience translating governance, risk, privacy, and security requirements into product capabilities and workflows.
• Experience defining a product where precedent is limited, including making and defending scope and boundary decisions.
• Experience partnering across engineering, design, analytics, and business functions in large, global enterprise settings.
• Familiarity with iterative product development models such as Agile or Lean.
• MBA or master's degree (preferred).
• Experience in healthcare, life sciences, or another regulated industry (preferred).
• Experience driving adoption of an internal platform or shared capability across independent teams (preferred).
• Experience establishing AI governance, responsible-AI, or model risk practices in a product context (preferred).
• Exposure to AI-supported product discovery and decision-making practices (preferred).
• Experience working with teams across regions or time zones (preferred).
• Must have permanent work authorization in the United States.