Principal Product Manager

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Product Management

Principal Product Manager for AI-powered information discovery experiences, focusing on Copilot Chat and AI systems. The role involves defining product strategy at the intersection of search, ML, data platforms, and UX to improve information discovery and interaction. Success is measured by user ability to find relevant information, data-informed decisions, rapid iteration, and improved search/AI experience quality.

What you'd actually do

  1. Define the product vision, strategy, and roadmap for AI-powered search and retrieval capabilities.
  2. Partner with engineering and machine learning teams to improve how information is represented, discovered, and ranked.
  3. Drive investments that improve search quality, relevance, accuracy, and user satisfaction.
  4. Establish success metrics and evaluation frameworks to measure product effectiveness.
  5. Lead experimentation efforts and use data-driven insights to inform product decisions.

Skills

Required

  • Bachelor's Degree AND 8+ years experience in product/program management or software development
  • Ability to meet Microsoft, customer and/or government security screening requirements

Nice to have

  • 2 years' experience working on information retrieval, search relevance, or ranking systems.
  • 5 years' experience building AI-powered products or platforms.
  • 2 years' experience in working on fine-tuning projects.
  • Demonstrated experience in product management, software engineering or data science.
  • Solid analytical skills and ability to use data to drive decisions.
  • Excellent communication and stakeholder management skills.
  • Ability to thrive in ambiguous and fast-moving environments.
  • Familiarity with information retrieval, search relevance, ranking systems, or recommendation technologies.
  • Experience partnering closely with machine learning and applied science teams.
  • Knowledge of experimentation methodologies, evaluation frameworks, and product analytics.

What the JD emphasized

  • AI-powered search and retrieval capabilities
  • search quality, relevance, accuracy
  • experimentation efforts
  • AI-powered products or platforms
  • information retrieval, search relevance, or ranking systems
  • fine-tuning projects

Other signals

  • AI-powered information discovery
  • Copilot Chat
  • search relevance
  • ranking systems
  • data-driven product development
  • AI systems find, understand, and surface information