Technical Program Manager – AI Infrastructure / GPU Clusters

GMI Cloud; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

GMI Cloud is seeking a Technical Program Manager to drive end-to-end deployment of AI GPU clusters and oversee production readiness across data center infrastructures. You will coordinate with solution architects, engineers, vendors, and contractors to ensure timely delivery of scalable GPU infrastructure.

The role focuses on hardware BOM design, server architecture, and network integration, with responsibility for cross-region collaboration and field deployment management in a fast-paced AI

Qualifications

• 5+ years experience in technical program or infrastructure project delivery.
• Experience with GPU cluster deployments or high-performance computing environments.
• Familiarity with GPU server architecture and distributed computing infrastructure.
• Experience working with Infrastructure Solution Architects to define system architecture and hardware BOM.
• Experience managing data center hardware deployments and system integration.

Responsibilities

• Lead the end-to-end deployment of AI GPU clusters, from infrastructure planning through production launch.
• Drive coordination across Infrastructure Solution Architects, network engineers, hardware vendors, and data center teams.
• Manage delivery timelines covering hardware deployment, network integration, cluster bring-up, and production readiness.

Skills

Technical Program Management

HPC infrastructure

GPU cluster deployments

Cross-region coordination

Job description

GMI Cloud is building next-generation AI infrastructure designed for large-scale GPU training and inference workloads. Our platform supports high-density GPU clusters deployed in modern data centers across multiple regions.

We are looking for a Technical Program Manager (TPM) to drive the deployment and delivery of GPU cluster infrastructure. This role will work at the intersection of AI hardware platforms, high-performance networking, and data center infrastructure, coordinating across solution architects, engineering teams, vendors, and contractors to deliver production-ready AI clusters.

Responsibilities

• Lead the end-to-end deployment of AI GPU clusters, from infrastructure planning through production launch.
• Drive coordination across Infrastructure Solution Architects, network engineers, hardware vendors, and data center teams.
• Manage delivery timelines covering hardware deployment, network integration, cluster bring-up, and production readiness.

Infrastructure Architecture Collaboration

• Work closely with Infrastructure Solution Architects (SA) to define:
• GPU server platform selection
• Network architecture for distributed GPU clusters
• Storage integration and cluster infrastructure design
• Support development of the cluster Bill of Materials (BOM) including compute, networking, storage, and supporting infrastructure components.
• Ensure architecture decisions align with data center constraints such as power density, cooling capacity, and rack layout.

System Integration

• Drive system integration for large-scale GPU clusters, including:
• GPU server deployment and configuration
• High-speed network topology implementation
• Power and cooling readiness
• Ensure deployments align with vendor reference architectures and validated cluster designs.

Contractor & Field Deployment Management

• Work closely with General Contractors (GC) and system integrators to manage on-site infrastructure implementation.
• Lead contractor onboarding, including SOW development, scope definition, and delivery milestone alignment.
• Coordinate and oversee field deployment activities such as:
• Structured cabling installation
• Rack installation and equipment mounting
• Network and power connectivity preparation
• Hardware staging and deployment logistics

Cluster Validation & Performance Testing

• Coordinate cluster bring-up and validation activities including:
• Single-node GPU validation
• Drive cluster benchmarking, stress testing, and performance verification before production release.

Operational Readiness

• Ensure deployed GPU clusters are fully ready for production workloads by driving:
• Hardware and network validation
• Monitoring and telemetry integration
• Operational documentation and runbooks
• Handover to operations teams

Required Qualifications

• 5+ years experience in Technical Program Management, Infrastructure Program Management, or HPC infrastructure delivery
• Experience with GPU cluster deployments or high-performance computing environments
• Familiarity with GPU server architecture and distributed computing infrastructure
• Experience working with Infrastructure Solution Architects to define system architecture and hardware BOM
• Experience managing data center hardware deployments and system integration
• Ability to coordinate multi-vendor infrastructure projects across regions

Preferred Qualifications

• Experience deploying large-scale AI infrastructure or GPU clusters
• Familiarity with:
• InfiniBand / RoCE / high-speed Ethernet networking
• rack elevation and high-density rack deployment
• Experience with cluster validation and performance benchmarking
• Background as Systems Engineer, HPC Engineer, or Infrastructure Architect
• Experience working in AI infrastructure, cloud infrastructure, or hyperscale data centers

Nice to Have

• Experience deploying liquid-cooled GPU clusters or high-power racks
• Experience working with NVIDIA AI infrastructure platforms
• Familiarity with AI training environments and distributed workloads