Senior Technical Program Manager, Global AI Scaling

Microsoft•Redmond, WA

15h•$119,800 - $261,000

About The Position

Cloud Operations + Innovation (CO+I) is the organization that builds, operates, and continuously evolves the infrastructure behind the Microsoft Cloud, powering services used by more than 95% of Fortune 500 companies. CO+I is responsible for the full datacenter lifecycle from global planning and site acquisition through design, construction, deployment, operations, and eventual decommissioning, spanning 400+ datacenters across more than 70 Azure regions and connected by one of the world's largest global networks. The CO+I AI Delivery organization is responsible for enabling the next generation of hyperscale AI capacity. The team works across engineering, datacenter planning, deployment, operations, supply chain, and product organizations to translate rapidly evolving AI technologies into scalable, production-ready infrastructure solutions delivered around the world.

Requirements

Bachelor's Degree AND 4+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
2+ 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 in Electrical Engineering, Mechanical Engineering, Computer Science, Industrial Engineering, Business or related field AND 6+ years of experience in Technical Program Management, Engineering, Product Management, Infrastructure Delivery, Hardware Deployment, Datacenter Infrastructure, Technology Strategy or related disciplines OR equivalent experience
Experience with datacenter power systems, cooling systems, networking infrastructure, electrical systems, or facility design considerations
Experience with GPU-based infrastructure, AI clusters, accelerated computing platforms, or large-scale AI hardware deployments
Experience evaluating infrastructure feasibility, deployment readiness, operational readiness, or technology introduction programs
Experience supporting the launch and scaling of new technology platforms in production environments
Knowledge of supply chain planning, manufacturing, deployment operations, or infrastructure scaling processes
Experience working across engineering, operations, and business organizations to deliver complex technology programs
Passion for solving difficult technical problems and enabling the next generation of cloud and AI infrastructure
Experience with hyperscale cloud infrastructure, AI infrastructure, datacenter delivery, hardware deployment, or large-scale technology deployment programs
Experience driving ambiguous technical challenges to resolution through structured analysis, technical leadership, and cross-functional collaboration
Demonstrated ability to influence outcomes and drive alignment across organizations without direct authority

Responsibilities

Lead readiness efforts for next-generation GPU infrastructure, ensuring datacenter, deployment, operational, and supply chain requirements are understood and incorporated into future deployment plans.
Partner across engineering, supply chain, datacenter design, deployment, and operations teams to assess the impact of new AI hardware technologies and enable successful global adoption at scale.
Support development of improved deployment methodologies to increase speed, predictability, scalability, and operational readiness for future generations of AI infrastructure.
Collaborate with stakeholders to establish scalable processes and frameworks that support rapid worldwide deployment of new GPU technologies.
Drive infrastructure-related feasibility assessments for new programs, identifying technical risks, dependencies, constraints, and readiness gaps associated with emerging AI platforms.
Lead cross-functional efforts to resolve complex technical challenges related to datacenter infrastructure, power, cooling, deployment readiness, and operational scale.
Translate technical risks, infrastructure tradeoffs, and deployment challenges into actionable recommendations for leadership and partner organizations.
Capture and operationalize lessons learned from large-scale AI infrastructure deployments to improve future delivery efficiency, quality, and scalability.
Drive alignment across a broad range of stakeholders to identify practical, technically sound solutions that balance business objectives, deployment timelines, and infrastructure constraints.
Contribute to planning and execution activities that shape Microsoft's future AI infrastructure deployment capabilities.