Senior Manager, AI Cluster Deployment

Role Description

We are seeking an experienced Senior Manager of AI Cluster Deployment to lead the planning, deployment, integration, and operational readiness of large-scale AI infrastructure environments. This role is responsible for delivering production-grade GPU clusters that support AI training, inference, and high-performance computing workloads across cloud, hybrid, and on-premises environments.

The ideal candidate brings deep technical expertise in GPU infrastructure, networking, storage, automation, and datacenter deployment, combined with strong program leadership and cross-functional execution skills. This leader will oversee end-to-end AI cluster deployment initiatives, including hardware integration, rack-and-stack operations, provisioning automation, performance validation, and operational handoff.

The role requires hands-on familiarity with modern AI infrastructure tooling and architectures, including Canonical MaaS, VAST Data storage platforms, and both InfiniBand and Ethernet-based GPU networking fabrics.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or related field (or equivalent experience).
• 10+ years of infrastructure engineering or datacenter deployment experience.
• 5+ years leading deployment or operations teams supporting large-scale AI, HPC, or GPU infrastructure.
• Hands-on experience deploying and operating large GPU clusters in enterprise or hyperscale environments.
• Strong expertise with:
  • Canonical MaaS
  • Data storage platforms
  • InfiniBand and Ethernet GPU fabrics
  • Network architecture
  • Linux systems administration
  • GPU server architectures
• Strong understanding of:
  • RDMA and RoCE networking
  • High-performance storage architectures
  • Cluster automation and provisioning
  • Datacenter infrastructure operations
• Proven ability to manage complex cross-functional infrastructure deployment programs.

Requirements

• Experience deploying NVIDIA DGX SuperPOD or similar AI infrastructure solutions.
• Familiarity with:
  • NVIDIA networking technologies
  • Spectrum-X or Quantum platforms
  • AI model training infrastructure
  • Liquid cooling environments
  • DCIM and observability platforms
• Experience in hyperscale, cloud, or AI infrastructure environments.
• Certifications in networking, Linux, Kubernetes, or cloud infrastructure are a plus.

Benefits

• Equal opportunity employer.
• We evaluate all qualified applicants without regard to race, religion, gender, age, national origin, disability, sexual orientation, veteran status, or other protected status.