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Microsoft

Principal Technical Program Manager, AI Supercomputer Operations

United States, Multiple LocationsManager or leadOperations

Listed on Microsoft’s official careers site. Posted October 12, 2026. Check that it is still open and apply there.

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Job description

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.

Bachelor's Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development 3+ years of experience managing cross-functional and/or cross-team projects. 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.

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