Technical Program Manager, Supercomputing

Microsoft AI•Mountain View, CA

2d•$165,600 - $331,200

About The Position

Microsoft AI is hiring a Technical Program Manager to organize and drive the end-to-end portfolio for delivering and operating the large-scale AI infrastructure supporting Microsoft AI. The role connects programs across the infrastructure lifecycle—Buildout, Bring-up, and Operationalize—and partners with MAI leadership, Supercomputing engineering teams, capacity and infrastructure owners, and Azure organizations to translate strategy and capacity needs into coordinated execution. The role establishes operating mechanisms connecting priorities, execution, risks, dependencies, and decision-making across Supercomputing programs. It requires technical fluency across datacenter infrastructure, compute, GPU systems, networking, storage, cluster bring-up, schedulers, platform services, and production operations, along with program leadership to drive complex initiatives across organizational boundaries. The position is identified as Technical Program Management IC6. The typical U.S. base pay range is $165,600–$296,400 per year; the range for the San Francisco Bay Area and New York City metropolitan area is $220,800–$331,200 per year. The position will be open for at least five days, with applications accepted on an ongoing basis until filled.

Requirements

Significant experience in technical program management, infrastructure engineering, capacity delivery, datacenter infrastructure, HPC, AI infrastructure, or large-scale distributed systems.
Demonstrated experience leading large, complex portfolios spanning multiple engineering and infrastructure organizations.
Experience driving programs across infrastructure lifecycle stages, such as capacity planning, datacenter buildout, infrastructure delivery, cluster bring-up, validation, production readiness, and operations.
Technical fluency in large-scale AI/HPC infrastructure, including accelerators, compute, networking, storage, schedulers, capacity, telemetry, datacenter infrastructure, and distributed systems.
Ability to translate organizational strategy and technical requirements into structured programs, milestones, dependencies, readiness criteria, and execution mechanisms.
Experience managing complex cross-organizational dependencies and driving execution where ownership is distributed across multiple teams.
Ability to build relationships and influence engineering and infrastructure organizations without formal authority.
Experience establishing executive operating rhythms, portfolio reviews, risk-management mechanisms, and decision frameworks.
Excellent written and verbal communication skills, including the ability to translate complex infrastructure topics into clear outcomes, risks, decisions, ownership, and actions for leadership.

Nice To Haves

Experience delivering GPU or accelerator-based AI/HPC capacity at datacenter or fleet scale.
Experience coordinating infrastructure programs spanning datacenter construction or buildout, hardware deployment, networking, storage, cluster bring-up, validation, and production operations.
Experience partnering across large cloud-provider organizations on infrastructure delivery, capacity management, or production readiness.
Experience establishing portfolio-level mechanisms for capacity planning, cluster readiness, utilization, reliability, and operational health.
Experience serving as a technical program manager for a technically complex engineering or infrastructure organization.

Responsibilities

Own the end-to-end Supercomputing program portfolio across Buildout, Bring-up, and Operationalize, establishing a lifecycle from infrastructure delivery through production readiness and ongoing operations.
Translate MAI strategy, model roadmaps, and capacity requirements into coordinated priorities, milestones, dependencies, and execution plans.
Structure programs connecting datacenter buildout, capacity delivery, hardware and network readiness, cluster bring-up, validation, workload certification, and transition into production.
Define readiness gates and exit criteria between lifecycle stages so capacity transitions predictably between teams and stages.
Drive cross-functional execution across Supercomputing, AI Infrastructure, capacity, datacenter, compute, networking, storage, scheduling, platform, and operations teams.
Lead Azure partner engagement by establishing operating rhythms, ownership models, escalation paths, dependency tracking, and joint planning mechanisms between MAI and Azure organizations.
Represent MAI requirements and priorities in Azure infrastructure discussions and make partner commitments, risks, and dependencies visible to Supercomputing leadership.
Create an integrated portfolio view of capacity, milestones, readiness, risks, dependencies, and operational health for leadership.
Identify cross-program risks and systemic bottlenecks across infrastructure buildout, cluster readiness, capacity availability, validation, and production operations.
Establish executive operating mechanisms, including portfolio, milestone and readiness, risk, and partner reviews, as well as leadership decision forums.
Connect Supercomputing priorities with execution and ensure decisions lead to clear ownership, actions, and measurable outcomes.
Drive alignment and accountability around shared infrastructure and capacity outcomes across MAI and Azure without formal authority.
Communicate Supercomputing strategy, portfolio health, critical milestones, risks, trade-offs, and decisions to senior leadership clearly and actionably.