Principal Technical Program Manager - Applied Science

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Technical Program Management

Principal Technical Program Manager for the OneDrive and SharePoint Applied Science team, focusing on driving high-ambition applied research in areas like agentic AI, retrieval, and content understanding to reshape knowledge management within Microsoft 365. The role involves shaping strategy, managing complex science-heavy initiatives, and ensuring scientific advancements translate into product and platform impact, with a focus on enabling invention at scale and influencing organizational direction.

What you'd actually do

  1. This role works in close partnership with Applied Science leadership and broader product leadership, including Engineering, Product Management, Design, and key partner organizations, to help shape and drive the applied science strategy across ODSP.
  2. The focus is on advancing both high‑value scientific investments that deliver clear product and customer impact and high‑ambition efforts that push the frontier of applied AI, focused on knowledge work.
  3. You will collaborate with leaders to inform portfolio‑level decisions spanning exploratory research, applied invention, and scaled product impact, helping surface tradeoffs, clarify priorities, and ensure different kinds of science are intentionally cultivated and sustained.
  4. Acting as a technical program manager for complex, science‑heavy initiatives, such as agentic systems, evaluation frameworks, knowledge retrieval, and content understanding, you will help define success in terms of scientific progress and learning, not just near‑term delivery.
  5. Along the way, you will support the translation of ambitious ideas into enduring capabilities, align teams on paths from concept to scale, and help build the narratives and mechanisms that allow bold science to consistently turn into durable impact.

Skills

Required

  • Bachelor's Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
  • 3+ years of experience managing cross-functional and/or cross-team projects.
  • Solid technical depth and comfort engaging with applied science, AI systems, experimentation, and evaluation.

Nice to have

  • Bachelor's Degree AND 10+ years experience engineering, product/technical program management, data analysis, or product development OR equivalent experience.
  • 8+ years of experience managing cross-functional and/or cross-team projects.
  • 1+ year(s) of experience reading and/or writing code (e.g., sample documentation, product demos).
  • Experience working closely with applied research or applied science teams.
  • Demonstrated strategic vision for applied science, with the ability to connect frontier scientific ideas to durable product and platform impact.
  • Track record of enabling high‑ambition, invention‑driven work in product environments, including shaping execution models for frontier technologies.
  • Exceptional ability to synthesize complex scientific work into clear strategic narratives that inform leadership decision‑making.

What the JD emphasized

  • high-ambition applied research
  • shaping applied science strategy
  • push the frontier of applied AI
  • portfolio-level decisions
  • complex, science-heavy initiatives
  • agentic systems
  • evaluation frameworks
  • knowledge retrieval
  • content understanding
  • scientific progress and learning
  • ambitious ideas
  • concept to scale
  • bold science
  • durable impact
  • Solid technical depth and comfort engaging with applied science, AI systems, experimentation, and evaluation.
  • Demonstrated strategic vision for applied science
  • Track record of enabling high‑ambition, invention‑driven work
  • shaping execution models for frontier technologies
  • Exceptional ability to synthesize complex scientific work into clear strategic narratives

Other signals

  • applied research
  • agentic AI
  • large-scale retrieval and reasoning
  • content understanding
  • evaluation-driven development
  • human-AI collaboration
  • product and platform impact
  • scientific ambition
  • organizational influence
  • invention at scale
  • knowledge work
  • portfolio-level decisions
  • exploratory research
  • scaled product impact
  • agentic systems
  • evaluation frameworks
  • knowledge retrieval
  • content understanding
  • concept to scale
  • durable impact