GPU Infrastructure Deployment Program Manager

The GPU Infrastructure Deployment Program Manager will lead the end-to-end execution of complex GPU cluster deployments supporting next-generation AI infrastructure.
You will oversee multiple concurrent programs, coordinating activities from contract signature through hardware installation, provisioning, acceptance testing, and customer go-live.
Working at the intersection of data centers, GPU architecture, networking, hardware manufacturing, and enterprise technology, you will ensure that every deployment progresses efficiently.
You will collaborate directly with OEM manufacturers, infrastructure providers, technical teams, enterprise customers, and senior executives.
A key focus will be managing critical paths, dependencies, risks, budgets, and delivery timelines across multiple deployment locations.
You will also translate complex technical progress into clear reporting for customers, executive leadership, and the Board.
This remote opportunity offers significant ownership, exposure to large-scale AI infrastructure projects, and the chance to shape scalable deployment processes in a fast-growing environment.

• Lead multiple concurrent GPU cluster deployment programs from contract signature through customer go-live.

• Develop and maintain detailed, dependency-aware project plans covering all deployment workstreams.

• Establish and monitor project milestones, critical paths, schedules, dependencies, and delivery priorities.

• Ensure deployment activities remain coordinated and aligned with contractual commitments and customer timelines.

• Drive predictable execution across the full deployment lifecycle, from initial planning to final acceptance.

• Track OEM hardware manufacturing, shipment, delivery, installation, and provisioning schedules.

• Coordinate data center readiness, including facility build-out, power, cooling, rack installation, and other infrastructure requirements.

• Manage network and connectivity dependencies in collaboration with network service providers.

• Coordinate directly with OEM manufacturers, data center operators, network and connectivity providers, managed service providers, and other external partners.

• Work closely with GPU cluster architecture, data center operations, procurement, supply chain, and deployment teams.

• Maintain working oversight of hardware installation, network turn-up, provisioning, and acceptance testing activities.

• Maintain visibility into project status, critical paths, risks, bottlenecks, dependencies, and mitigation plans across simultaneous deployments.

• Identify potential issues early and coordinate corrective actions before they affect schedules or budgets.

• Manage risks, issues, escalations, and cross-functional dependencies throughout the deployment lifecycle.

• Ask informed technical questions to identify missing requirements, schedule risks, and potential delivery constraints.

• Provide enterprise customers with clear progress updates, translating technical project status into meaningful go-live planning information.

• Prepare executive and Board-level reports covering deployment progress, risks, dependencies, schedule impacts, and financial considerations.

• Maintain effective communication across technical, operational, commercial, and executive stakeholders.

• Support the development of repeatable deployment processes as the organization expands its infrastructure operations.

The ideal candidate has substantial program management experience in complex infrastructure environments and direct, hands-on exposure to GPU cluster deployments. They should combine technical understanding with strong planning, risk management, and stakeholder communication capabilities. Key qualifications include:

• At least seven years of program or project management experience supporting data centers, infrastructure, telecommunications, or large-scale technology deployments.

• Direct experience managing GPU cluster deployments from planning through implementation or customer go-live.

• Demonstrated ability to manage multiple complex infrastructure projects simultaneously.

• Strong understanding of GPU cluster architecture and the complete deployment lifecycle.

• Experience coordinating data center readiness, hardware delivery and installation, network turn-up, vendor dependencies, and acceptance testing.

• Experience working directly with OEM manufacturers, data center operators, and network or connectivity providers.

• Strong expertise in risk, issue, dependency, and critical-path management.

• Experience preparing project reports for enterprise customers and executive or Board-level stakeholders.

• Proficiency with project management platforms such as Smartsheet, Microsoft Project, Jira, Confluence, Asana, or equivalent tools.

• Excellent communication and organizational skills, with the ability to work effectively with technical specialists, operational teams, executives, and customers.

• Ability to understand the technical aspects of GPU infrastructure deployments and identify potential bottlenecks through informed discussions with engineering teams.

• Must be a U.S. citizen.

• PMP certification or equivalent project management qualification is preferred.

• Experience in a neocloud, hyperscaler, GPU infrastructure provider, or comparable large-scale compute environment is strongly preferred.

• Familiarity with NVIDIA Reference Architecture and GPU cluster acceptance testing standards is an advantage.

• Annual base salary range of $120,000–$200,000.

• Competitive performance-based bonus opportunity.

• Equity opportunity.

• Health insurance.

• Dental insurance.

• Vision insurance.

• Life insurance.

• Paid time off.

• Retirement plan.

• Remote work flexibility from anywhere in the United States.

• Opportunities to work on advanced GPU and AI infrastructure deployments.

• Direct collaboration with specialists across GPU architecture, data centers, networking, and supply chain.

• Exposure to executive leadership and strategic business decisions.

• Opportunities to develop expertise across the full GPU cluster deployment lifecycle.

• Opportunity to help establish scalable deployment processes in a growing organization.