At Microsoft Research, we are shaping the future of AI infrastructure by pursuing high-risk and high-reward programs that will define the next generation of AI platforms. Our work spans the full stack, models, systems, software, and hardware, and we partner with product teams across Microsoft to turn research breakthroughs into impact at scale. Through close collaboration with industry partners, the team bridges research and production, translating hardware innovation into working prototypes and manufacturable solutions for next-generation AI infrastructure. You will join a multidisciplinary team working at the intersection of optics, electronics, photonics, packaging, networking, and AI system design.

As a Principal Technical Program Manager, you will translate early-stage ideas from Microsoft Research and applied R&D into shippable products and services. You will partner closely with researchers to shape technical concepts into product roadmaps, drive execution alongside Azure engineering teams to bring those capabilities to cloud AI scale, and manage relationships with external hardware and software suppliers to land critical dependencies on time and on spec. You will own program structure, technical trade-offs, and cross-team alignment from prototype through general availability. This opportunity will allow you to deepen your technical breadth across cutting-edge research and large-scale cloud and AI systems, build an influential network spanning Microsoft Research, Azure, and our supplier ecosystem, and grow as a senior program leader operating at the intersection of innovation and production.

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.

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  You will translate early-stage research from Microsoft Research and applied R&D into shippable cloud AI capabilities, shaping technical concepts into product roadmaps with researchers, driving execution with Azure engineering teams, and managing external hardware and software suppliers to land critical dependencies on time and on spec.

• You will partner with MSR researchers, Azure engineering teams, and external hardware and software vendors to design technical solutions that span models, systems, and hardware. You will surface the trade-offs and risks behind those choices and make data-driven recommendations to research and engineering leads, and supplier partners.

• You will define what success looks like for moving research prototypes to general availability, the technical bar, the launch criteria, and the cross-team commitments, and hold MSR, Azure, and supplier stakeholders aligned to it through every program milestone.

• You will own the program structure end-to-end: roadmap, schedule, staging and rollout plans, and governance for multi-team, multi-quarter efforts that cut across MSR, Azure, and the supplier ecosystem.

• You will close the loop from production back to research: validate use cases against live workloads, instrument performance and reliability metrics at cloud AI scale, and bring signal from customer engagements back to MSR and Azure teams to shape the next generation of platform investments.

Required/Minimum Qualifications

• Master's or PhD Degree in computer engineering, electrical/electronic engineering, computer science, physics, applied physics, optics/photonics, materials science, or a related field 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.

• Ability to operate effectively in a multi-disciplinary environment.

• Excellent communication skills in English, both written and spoken, including the skill to clearly communicate technical results and justify assumptions to diverse technical audiences.

• Basic understanding of optics and/or photonics, sufficient to engage with researchers and suppliers on technical trade-offs in optical systems.

Additional or Preferred Qualifications

• Experience working on research or industry projects related to AI systems design.

• Knowledge of networking and interconnects, broadly defined — datacenter networking, high-speed interconnects, fabrics, or related areas.

• Familiarity with hardware/system simulation or modeling tools.

• Knowledge of advanced packaging, co-packaged optics, or memory hierarchies.