Cluster Solution Architect

What you'll do

• Design and optimize integrated AI inference and training architectures, balancing performance, efficiency, operational needs, and deployment feasibility.
• Translate customer requirements into technical recommendations, proposals, RFP/RFQ responses, bills of materials, presentations, proofs of concept, and demonstrations.
• Guide customer engagements and collaborate with sales, engineering, deployment, hardware, networking, and supply chain teams to validate solutions.

What they ask for

• Bachelor's degree in a related engineering field; other educational backgrounds will also be considered with sufficient relevant technical knowledge.
• 10+ years of experience in data center infrastructure, solution architecture, systems engineering, pre-sales engineering, or technical consulting.
• Experience with large-scale AI inference and training workloads, including LLM infrastructure, model serving, capacity planning, performance optimization, and production deployment.
• Experience designing, supporting, or deploying customer-facing AI infrastructure, GPU clusters, HPC environments, or large-scale data center architectures.

Nice to have

• Master's degree or PhD in a related engineering field.
• 5+ years preparing or contributing to RFP/RFQ responses, ideally for NVIDIA HGX or DGX platforms.

Tools

NVIDIA AI Enterprise, Dynamo, NIM, NVIDIA Infrastructure Controller (NICo), Mission Control, InfiniBand, RoCE, Python

AI focus

Designs AI inference and training infrastructure, primarily large-scale inference architecture, software integration, optimization, and production GPU cluster deployment.