Senior Technical Program Manager - Applied Science

The Applied Science team in Developer Division builds the intelligence behindGitHub Copilot, VS Code, and Visual Studio- products used by tens of millions of developers daily. We partner with product teams acrossseveralactive science projects, driving evaluation, model integration, and responsible AI at a scale few teams in the industry can match.

We'rea team of builders. We ship fast, measure rigorously, and iterate. We believe the most impactful AI safety work happensinsideproduct teams - embedded alongside the scientists and engineers building the models - not in separate review boards or governance committees.

Youwill be joining at a moment of significant expansion, helping define what responsible AI at product scale looks like for the next generation of developer tools.

We'relooking for a Technical Program Manager who can own the responsible, safe, and compliant delivery of AI capabilities,not from the sidelines, but embedded deep in the technical details alongside applied scientists and engineers.You'llshape how models get evaluated, how features ship safely, and how privacy-by-design becomes muscle memory across the organization.This is a high-uncertainty, high-impact domain. Requirements change as models evolve, and the program management playbook is still being written.You'llneed to be comfortable shaping the path as you walk it.

In this role, you will:

• Own Responsible AI delivery end-to-end-Serve as the lead Responsible AI (RAI) ChampionforGitHub Copilotfeatures,partnering closely with applied scientists, engineers, and product teams to drive daytoday RAI execution for model and product releases, ensuring release readiness through consistent application of required governance, safety evaluations, monitoring plans, and compliance checkpoints as products, models, and RAG scenarios evolve.

• Influence and drive evaluation quality and coverage -Partner with applied science engineeringto own the deployment and continuous execution of Responsible AI (RAI) and safety evaluations for product releases, including maintaining and evolving evaluation suites as requirements, models, and product scenarios change, andown the execution of the RAI monitoring planto ensure ongoing compliance and signal detection postdeployment.

• Drive cross-functional coordination at scale-Operate across product and science teams,maintainingprogram plans including task assignments, dependencies, and resource allocations, driving execution and monitoring progress against milestones;Establish and track success metrics (KPIs) for AI model quality and program efficiency; communicate progress and risks to stakeholders and leadership.

  • Embed privacy-by-design across the ML lifecycle- from data pipelines and dataset curation through model training, evaluation, and production deployment. Ensure privacyandcompliance (ex: GDPR, CCPA) is built into the workflowby design.
  • Build the playbook- this is an emerging discipline.You'lldefine processes, create frameworks, andestablishthe program management infrastructure for responsible AI delivery. Much of what you build will be first-of-its-kind.