Technical Program Manager – AI Infrastructure / GPU Clusters

Posted 5 days ago

gmi cloudSacramento (CA)

Computer and Information Systems Managers Computer Systems Design Services

SENIORITY

Manager

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About the role

About the Company: 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.

About the Role: 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:

GPU Cluster Deployment 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: Rack elevation planningGPU 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
Multi-node cluster deploymentGPU interconnect validation (P2P, RDMA)
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 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 BOMExperience managing data center hardware deployments and system integration
Ability to coordinate multi-vendor infrastructure projects across regions Required SkillsExperience deploying large-scale AI infrastructure or GPU clusters
Familiarity with: InfiniBand / RoCE / high-speed Ethernet networkingGPU interconnect validation (P2P / RDMA)
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 Preferred SkillsExperience deploying liquid-cooled GPU clusters or high-power racks
Experience working with NVIDIA AI infrastructure platforms
Familiarity with AI training environments and distributed workloads

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