[Hiring] Principal Technical Program Manager - Applied Science @Microsoft

Role Description

AI evaluations are at a critical inflection point. Static benchmarks are saturated; benchmarks like MMLU, HumanEval, and SWE-Bench have reached their limits as models become increasingly familiar with public test data, and capable of autonomously finding answer keys online. The gap between benchmark scores and real developer experience is growing, making it hard to understand which problems are truly ‘solved’, and which are worth deeper investment.

GitHub is uniquely positioned to lead the industry through this transition. We have direct feedback and deep insight into real production workflows from millions of developers, and the scale to build evaluation systems that truly reflect developer success. We’re looking for a Principal Technical Program Manager to help us build the future of AI evaluation.

The Applied Science team for GitHub Copilot sits at the intersection of frontier AI research and the world's largest developer platform. We ship AI-powered experiences (ex: code completion, code review, coding agents) used by millions of professional developers every day. As a member of the team, you will help lead GitHub Copilot's AI evaluation strategy end-to-end — from benchmark design and lifecycle governance, through evaluation infrastructure and internal adoption, to community engagement and public transparency. You are the person who ensures that every model swap, product harness, and feature launch is measured against what actually matters to developers — and that the world can see the results.

Responsibilities

• Partner with Applied Science researchers to translate cutting-edge evaluation research into production systems: adaptive testing (IRT), agent-centric co-evolution, adversarial benchmarking, and telemetry-driven benchmark generation.
• Lead the deprecation of saturated benchmarks and design their next-generation replacements — including procedurally-generated code evaluations that can't be memorized and adaptive testing systems that skip trivial questions for frontier models.
• Build GitHub's community benchmark submission program — enabling external researchers, enterprises, and open-source developers to contribute domain-specific evaluations — and publish GitHub's first external benchmark transparency reports showing how models perform on real developer workflows.
• Design and operationalize multi-tier evaluation frameworks — from fast automated regression suites and LLM-as-judge systems, through expert human evaluation, to production A/B testing — so teams can iterate in hours, not weeks.
• Design feedback-to-benchmark pipelines that convert thumbs-down signals, user frustrations, and support tickets into candidate regression tests — systematizing informal practices into scalable, automated systems.
• Establish evaluation as a first-class discipline across GitHub Copilot — creating the rituals, dashboards, and communication cadences that make evaluation results accessible and actionable for every team.

Qualifications

• 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.

Requirements

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years.

Preferred Qualifications

• 5+ years of experience in technical program management, product management, applied science, or equivalent.
• 2+ years managing programs in machine learning, AI/ML evaluation, or data science.
• 2+ years managing cross-functional and/or cross-team projects.
• Deep, firsthand experience with AI/ML evaluation methodologies: benchmark design and validity, human evaluation frameworks, automated scoring systems (including LLM-as-judge), A/B testing, and statistical significance.
• Deep personal experience with AI coding tools — you use Copilot, Cursor, Claude Code, or similar tools daily and have strong opinions about what "good" looks like from a developer's perspective.
• Understanding of software engineering workflows at scale — code review, CI/CD, testing, debugging, refactoring — and how AI tools should integrate into each.
• Experience with community or open-source program management — contributor programs, external research partnerships, or developer relations in a technical context.
• Proven ability to navigate competing priorities across teams and build shared commitment to common goals in ambiguous, fast-moving environments.
• Track record of building evaluation systems that directly influenced product or model shipping decisions at scale.

Compensation

The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances.