The role 

We are seeking a GPU Cluster Architect to drive the design of our next-generation AI infrastructure. In this high-impact, hands-on role, you will make end-to-end architectural decisions across compute, networking, and storage — ensuring our platforms can meet the massive scale, performance, and reliability requirements of modern AI workloads.

This is a high-impact, hands-on architecture role where you’ll define how tens of thousands of GPUs are interconnected, cooled down, powered, and optimized across multiple data center sites.

You are welcome to work remotely from the USA. 

Your responsibilities will include: 

• Cluster Design: Architect scalable GPU cluster topologies including compute nodes, interconnect (InfiniBand, Ethernet), storage, and control planes.
• Performance Modeling: Analyze AI/ML workloads (e.g. LLM training, inference) to inform design tradeoffs across latency, bandwidth, and GPU density.
• Network Architecture: Align with network architect relevant design and validate low-latency, high-throughput interconnects (e.g., InfiniBand HDR/NDR, RoCEv2) at POD and DC scale.
• Storage Integration: Work with storage teams to optimize performance for training datasets, checkpointing, and others.
• Reliability & Monitoring: Understand and analyze signal from monitoring systems to the detect flows in design
• Collaboration: Partner with site reliability, networking, storage, and DC engineering teams to operationalize and scale your architecture.

We expect you to have: 

• 5+ years of experience designing clusters.
• Deep understanding of modern GPU architecture (NVIDIA, AMD, etc.).
• Experience with HPC interconnects (InfiniBand & RoCE).
• Solid background in systems architecture, networking, and hardware reliability.
•  Experience in scripting for automation and telemetry pipelines (Python, Go, etc.)