Principal Technical Program Manager

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, connected by over 600,000 kilometers of fiber. As the engine that enables Microsoft's cloud-first mission, CO+I delivers reliable, trusted, secure, and sustainable cloud and AI infrastructure to meet customer growth and support Microsoft's broader mission to empower every person and organization to achieve more. The CO+I Artificial Intelligence (AI) Delivery organization is responsible for enabling Microsoft's next generation of hyperscale AI supercomputing capacity. The team has close collaboration throughout Microsoft, as these initiatives will be at the forefront of innovation, involving pilot programs and other experiments that shape our continued dedication to delivering AI platform services quickly and on a large scale.

AI Network Acceleration exists to make AI capacity delivery predictable, repeatable, and fast at global scale. This role is central to that mission. We are hiring a Principal Technical Program Manager (TPM) to drive design validation and readiness assessment for AI data center network infrastructure, with deep focus on GPU platforms, backend networks, and high-performance fabrics that power large-scale AI training and inference. This role will co-own backend network readiness with platform and engineering partners-ensuring that AI network designs are not only technically sound, but deployable, scalable, and operationally viable in real data centers. This is a high-impact role at the intersection of architecture, execution, and acceleration. This role directly determines how fast AI capacity reaches production. You will influence how GPU clusters and AI networks are validated, deployed, and scaled globally. Your work turns complexity into execution certainty.

This role is located either in one or all hub locations - Redmond, WA, Atlanta, GA, San Antonio, TX, Phoenix, AZ, or Washington DC. Relocation support will be provided, and successful candidates should relocate or reside within 50 miles of the hub office location. This role is hybrid work,3 days / week in-office"

Turn record-breaking AI infrastructure acceleration into the global operating standard. This role sits at the intersection of AI infrastructure engineering, data-center deployment, network architecture, capacity delivery, operational excellence, and organizational transformation.The Principal Technical Program Manager will take proven AI Network and GPU capacity acceleration practices-from design validation and deployment readiness through regional network readiness, infrastructure optimization, and deployment execution-and convert them into repeatable, measurable, and globally adopted capabilities.This is not a traditional program-management role.It is a technical execution and scaling leadership role designed for someone who can move comfortably between architecture conversations, critical-path deployment problems, executive decisions, engineering teams, regional operations, and global process transformation.The successful candidate will help provide solutions to make extraordinary deployment performance repeatable everywhere.

What You Will Do: Lead Global AI Infrastructure Deployment Acceleration: Own the development, training workforce and scaling of a global AI network and infrastructure acceleration operating model spanning Commercial Cloud, new AI regions, new data centers, colo expansions, and large-scale GPU deployments. Translate successful deployment practices into repeatable architectures, operating mechanisms, technical decision frameworks, runbooks and deployment patterns that can be reused globally.Identify where AI infrastructure delivery remains dependent on manual coordination, repeated escalation, organizational handoffs or individual expertise and systematically eliminate those dependencies.

Provide Deep Technical Program Leadership: Develop strong end-to-end understanding of the AI infrastructure deployment lifecycle and its critical dependencies across areas including:

• GPU infrastructure and large-scale AI clusters
• Data-center network architecture
• High-performance Ethernet and InfiniBand environments
• Front-end and back-end network infrastructure
• Regional and WAN connectivity
• RNG and IDF readiness
• Data-center fit-out and infrastructure readiness
• Capacity planning and deployment sequencing
• Facility/network dependencies
• Infrastructure validation and acceptance
• High-speed optical technologies and evolving network architectures
• Cloud and distributed infrastructure systems

The role is expected to challenge assumptions, recognize architectural and execution risks, facilitate technical decisions, and translate engineering complexity into actionable execution plans.This directly aligns with the L65 expectation to apply end-to-end technical expertise across related infrastructure and systems and use that expertise to drive scalable improvements.

Required Qualifications:

• Bachelor's Degree AND 6+ years experience inTechnical Program Management,AI Data center Infrastructure engineering,Cloud or data center platform delivery 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. These requirements include, but are not limited to the following specialized security screenings:
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Strong technical judgment with the ability to engage credibly with engineering partners.
• 6+ years' experience in AI data center infrastructure, GPU platforms, or hyperscale networking.
• Experience with one or more of the following:
  • Backend fabrics using InfiniBand and/or advanced technologies, including optics
  • Large-scale GPU clusters (training and/or inference)
  • High-density rack architectures, optics, and cabling systems
• Strong understanding of:
  • AI workload communication patterns
  • Backend network scale limits and failure modes
• Experience reducing deployment cycle time through:
  • Design standardization
  • Automation and tooling
  • Parallel bring-up and validation models
• Exposure to AI platform bring-up, capacity activation, or production readiness reviews.

#COICareers #IPECareers

Technical Program Management IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.