AI Cluster Architect

Overview

Architect large-scale GPU clusters within fixed site power budgets, determining the optimal GPU count across the full stack of compute, storage, networking, cooling and facility constraints.

What you'll do

• Architect large-scale GPU clusters within fixed site power budgets that optimizes for maximum GPU density while reserving necessary headroom for compute services, storage, and networking.
• Model and validate power consumption across the full cluster bill of materials (GPUs, CPUs, NICs, switches, fabric components, storage, and facility limits).
• Evaluate tradeoffs across multiple fabric networking architectures (InfiniBand, RoCE, SpectrumX) as well as multi-plane, 2-tier/3-tier, and rail-optimized topologies.
• Determine network scale limits based on switch radix, link speed, topology, and blocking requirements.
• Gather, interpret, and maintain detailed SKU-level power and thermal specifications for GPUs, NICs, switches, DPUs, storage, and server platforms.
• Develop power-aware cluster configuration templates and capacity-planning models that can scale across sites with varying constraints and allow for quick iteration and ideation.
• Document architecture, design choices, tradeoff analyses, and operational considerations for deployment and lifecycle management.
• Provide guidance on future-proofing, including the ability to incorporate next-gen GPUs, NICs, or fabrics.
• Collaborate with vendors on novel fabric architectures that enable large-scale cluster deployments (100k+ GPUs).

What you'll need

• 7+ years designing or building large-scale HPC, AI, or hyperscale GPU clusters.
• Expert understanding of GPU and accelerator system design, including node topology, PCIe/NVLink/NVSwitch/ROCm, and NIC-to-GPU affinity considerations.
• Strong familiarity with InfiniBand, RoCE, and SpectrumX networking, including multi-tier, multi-plane, Clos/dragonfly variants, and large-radix switch design.
• Demonstrated experience modeling power draw and thermal characteristics of servers, GPUs, NICs, switches, optics, and storage systems.
• Ability to design networks that maintain full non-blocking performance or intentionally introduce over/under-subscription while understanding impacts on workload performance.
• Proven ability to gather and analyze vendor SKU-level specifications and incorporate them into scalable cluster architectures.
• Experience balancing customer-driven requirements for compute, storage, and service density in combination with overall GPU count.
• Strong documentation, communication, and cross-functional collaboration skills.

Details

• Location: Remote, United States.
• Compensation: $200,000 - $220,000, final compensation varies by experience, background/skill set, location, and applicable laws.