Senior Solution Engineer – GPU & AI Infrastructure

Role overview Act as the technical architect for enterprise AI and high-performance computing infrastructure, partnering with commercial teams from customer discovery through deployment. Translate workload and business needs into GPU cluster designs, technical proposals, and implementation guidance across bare-metal and cloud-native environments.

Responsibilities - Produce high- and low-level designs, rack diagrams, and detailed bills of materials for GPU clusters. - Design scale-up and scale-out topologies using NVIDIA GPU systems, NVLink/NVSwitch, InfiniBand, and RoCE fabrics. - Specify compute, networking, storage, cabling, power, and cooling components for proposed deployments. - Shape deployment approaches for bare-metal workloads using Slurm and OpenMPI, and Kubernetes environments using GPU and network operators. - Support technical discovery, proposals, and responses to complex infrastructure requests; validate designs through proofs of concept. - Guide customer onboarding and deployments, coordinate with hardware vendors and engineering teams, and relay customer needs to product teams.

Requirements - Five or more years in solution architecture, systems engineering, or technical pre- or post-sales work focused on AI, HPC, or high-performance cloud infrastructure. - Degree in a relevant engineering or computing field, or equivalent practical experience. - Experience supporting enterprise customers from technical discovery through implementation. - Deep familiarity with NVIDIA HGX/DGX systems, NVLink/NVSwitch, and current GPU platforms. - Expert knowledge of InfiniBand and RoCE/RoCEv2 networking, plus familiarity with GPUDirect RDMA or Storage. - Proficiency with GPU workloads on Kubernetes or bare-metal systems, and experience producing detailed design documents and bills of materials. - Strong communication and presentation skills, including explaining technical tradeoffs to senior stakeholders; ability to troubleshoot distributed training and inference bottlenecks.

Nice to have Relevant NVIDIA professional or associate certifications in AI infrastructure, AI networking, InfiniBand, or cloud-native AI workload deployment.

Benefits and work setup Remote work with flexibility and autonomy, an uncapped holiday policy, and a four-day work week except when attending events. Compensation and benefits are described as competitive.