Senior Product Manager - Foundry Inferencing & Training (coreai - Multiple Roles)

Microsoft Microsoft · Big Tech · Redmond, WA +4 · Product Management

Senior Product Manager for Microsoft's Foundry Inference & Training team, focusing on product strategy and execution for AI model platforms. The role involves owning product strategy for AI model training, inference, experimentation, and platform enablement, evolving model offerings, driving developer-facing experiences, and defining efficiency metrics. Collaboration with engineering, data science, finance, and go-to-market teams is key, with a focus on solutions for regulated environments.

What you'd actually do

  1. Own product strategy and roadmap across AI model training, inference, experimentation, and platform enablement, balancing near‑term delivery with long‑term scale
  2. Evolve model offerings across the Foundry portfolio, including onboarding and scaling partnerships with flagship providers, open-source ecosystems, and emerging model/tooling partners
  3. Drive developer-facing experiences - tooling, SDK workflows, documentation, and samples - so builders can integrate and ship on Foundry with low friction
  4. Define and track efficiency and growth metrics (utilization, cost, performance, adoption), and lead experimentation to validate hypotheses and drive optimizations
  5. Drive alignment across engineering, design, finance, marketing, and partner teams; manage dependencies and unblock execution in ambiguous environments

Skills

Required

  • Bachelor's Degree and 5+ years of experience in product/program management or software development
  • Ability to meet Microsoft, customer and/or government security screening requirements

Nice to have

  • Experience delivering AI, cloud services, developer tools, or platform products
  • Familiarity with model ecosystems
  • Experience applying compliance, privacy, safety, or governance considerations
  • Strong analytical skills
  • Background in platform/infrastructure domains
  • Exposure to GPUs or AI accelerators
  • Experience with SDK delivery mechanics
  • Proven ability to influence cross-functional stakeholders

What the JD emphasized

  • regulated and highly governed environments
  • AI model training, inference, experimentation, and platform enablement
  • developer-facing experiences
  • efficiency and growth metrics
  • alignment across engineering, design, finance, marketing, and partner teams

Other signals

  • AI model ecosystem
  • model training and inference platforms
  • developer tooling
  • ecosystem partnerships
  • regulated and highly governed environments