Technical Program Manager – Health AI Research

Overview

As a Technical Program Manager in Microsoft AI Health, you lead end-to-end health AI research programs, turning research goals into measurable outcomes. You collaborate with researchers, engineers, product teams, and compliance partners to align efforts and accelerate execution. You will shape goals, manage risks, and ensure launch readiness with safety and privacy considerations. This role offers impact at scale by advancing health AI across Microsoft’s consumer ecosystem. You’ll thrive in a fast, cross-functional environment that values rigorous delivery and responsible AI.

Responsibilities

• Shape goals and success metrics for health AI research programs and own end-to-end execution across model development lifecycle
• Coordinate cross-functional work across research, engineering, clinical, product, and compliance to translate requirements and unblock critical paths
• Steer model development and launch readiness against safety, quality, privacy, and clinical criteria; manage training/evaluation operations and compute planning
• Introduce lightweight operating mechanisms and maintain artefacts to keep teams aligned in fast-moving research
• Communicate progress, risks, and plans to leadership and advocate for needed resourcing and focus

Key requirements

• Several years of experience in technical program management delivering complex, cross-functional programs
• Experience delivering AI/ML programs across research, pretraining, post-training, or evaluation
• Technical fluency to reason about model training, evaluation, data, and infrastructure trade-offs with researchers and engineers
• Ability to bring clarity to complex, changing research challenges at pace
• Strong written and verbal communication; ability to influence without authority and align diverse stakeholders
• Collaborative, accountability-driven approach with continuous improvement mindset

• collaboration
• influence without authority
• strong communication
• AI/ML program management
• model training and evaluation concepts
• data and infrastructure trade-offs

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