Principal Technical Program Manager, AI Supercomputer Operations

Microsoft•,

10d•$142,800 - $304,200

About The Position

The world’s most advanced Artificial Intelligence (AI) workloads depend on infrastructure that must operate reliably at unprecedented scale. Our team operates Microsoft’s largest AI supercomputers, partnering with strategic AI customers and engineering teams to deliver the reliability and operational excellence required for large-scale AI training and inference workloads. As a Principal Technical Program Manager, AI Supercomputer Operations, you will lead the end-to-end operational programs for some of Microsoft’s most critical AI training supercomputers. You will serve as a trusted operational partner to strategic AI customers, bringing together customer priorities, infrastructure health, engineering execution, and business commitments to ensure training workloads run reliably. This is a highly cross-functional and customer-facing role spanning infrastructure availability, training reliability, incident management, repair and recovery, planned maintenance, and operational readiness. You will partner across multiple engineering teams, Business Development, and datacenter teams to manage operational risk and translate customer requirements and operational challenges into investments that improve infra reliability and scalability. 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.

Requirements

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.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Nice To Haves

Bachelor's Degree AND 12+ years experience engineering, product/technical program management, data analysis, or product development OR equivalent experience.
8+ years of experience managing cross-functional and/or cross-team projects.
1+ year(s) of experience reading and/or writing code (e.g., sample documentation, product demos).
1+ year(s) experience leading large, technically complex programs across multiple engineering organizations.
1+ year(s) experience with AI/ML infrastructure, high-performance computing, GPU infrastructure, distributed training, or hyperscale cloud platforms.
1+ year(s) experience with reliability engineering, incident management, infrastructure maintenance, or fleet operations.
1+ year(s) experience defining and driving operational metrics, SLAs, or other contractual service commitments.
1+ year(s) experience translating operational needs and recurring challenges into scalable and automated engineering solutions.

Responsibilities

Lead end-to-end operations for large-scale AI training supercomputers, establishing priorities, operating rhythms, accountability, and cross-team execution.
Drive successful execution of critical AI training workloads, proactively identifying infrastructure risks and coordinating teams to protect availability, reliability, and training progress.
Serve as a trusted operational partner to strategic AI customers, building strong relationships, communicating clearly during high-pressure situations, and translating customer priorities and feedback into action.
Deliver against customer and SLA commitments, using operational and reliability metrics to understand performance, identify risks, and drive corrective actions.
Lead response and recovery for complex infrastructure issues, bringing engineering teams together to quickly mitigate customer impact and restore capacity.
Turn operational learnings into scalable solutions, driving improvements in observability, automation, tooling, and operational processes across the Azure supercomputing fleet.