Principal Technical Program Manager
- Compensation
- Not disclosed
- Location
- United States, California, Mountain View
- Work setup
- Onsite
- Seniority
- Principal
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Project management
- Posted
Skills
Must have
- 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.
Nice to have
- Bachelor's Degree AND 12+ years experience engineering, product/technical program management, data analysis, or product development OR equivalent experience.
- Experience defining or operating metrics used for large-scale product decisions.
- Demonstrated ability to lead cross-functional initiatives across multiple teams.
- Solid analytical and quantitative problem-solving skills.
- Excellent communication and stakeholder management abilities.
- Experience in search, recommendation systems, ranking, AI products, or large-scale consumer experiences.
- Experience building evaluation frameworks for LLMs, retrieval systems, or generative AI applications.
- Familiarity with offline evaluation methodologies and human rating systems
- Experience partnering with Data Science, Applied Science, and Research organizations.
- Proven success driving strategy in ambiguous and rapidly evolving technical domains.
Full description
Overview
Microsoft Search is at the center of AI-powered experiences that help hundreds of millions of users find information, accomplish tasks, and make decisions every day. As search evolves more and more into AI-native experiences, measuring quality becomes one of the most important challenges in the organization.
We are looking for an experienced Principal Product Manager to lead the strategy and execution of Bing's offline quality measurement ecosystem. This role sits at the intersection of product management, evaluation science, data science, user research, and engineering.
You will define how we measure search quality, relevance, presentation, and competitive performance across Bing and Copilot Search experiences. The metrics and evaluation systems you build will directly influence product investment decisions, experimentation, model launches, and executive scorecards across Microsoft AI Experiences (aix).
This is a highly strategic role with broad organizational impact and significant executive visibility.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
- Define the future of quality measurement
- Own the long-term vision and roadmap for Bing's offline quality metrics ecosystem.
- Define measurement strategies for AI-powered search, answer experiences, ranking systems, retrieval, multimodal content, and agentic experiences.
- Identify gaps in existing quality measurements and drive invention of next-generation metrics.
- Lead metric design and validation
- Partner with Data Scientists, Applied Scientists, and Research teams to create robust, trustworthy, and actionable quality metrics.
- Drive metric validation, calibration, and governance frameworks.
- Ensure offline metrics accurately predict user value and align with online outcomes.
- Build organizational alignment
- Drive alignment across Search, Copilot, Answer Experiences, Ranking, Ads, Multimedia, and other partner teams.
- Influence product roadmaps through measurement-based insights.