Principal Technical Program Manager, AI Supercomputer Operations

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)

leading large, technically complex programs across multiple engineering organizations. 1+ year(s)

with AI/ML infrastructure, high-performance computing, GPU infrastructure, distributed training, or hyperscale cloud platforms. 1+ year(s)

with reliability engineering, incident management, infrastructure maintenance, or fleet operations. 1+ year(s)

defining and driving operational metrics, SLAs, or other contractual service commitments. 1+ year(s)

translating operational needs and recurring challenges into scalable and automated engineering solutions.