Senior Solutions Engineer

Salary: £? - ? per year

Requirements:

• We ideally want 5+ years of experience in one or more of the following areas: Solution Architecture, Technical Pre-Sales, Systems Engineering, HPC, AI / Machine Learning Infrastructure, GPU Infrastructure, or Data Centre Infrastructure.
• We need strong practical knowledge of NVIDIA GPU environments and an understanding of how large GPU clusters are designed, connected, and deployed.
• Experience with Blackwell, HGX, DGX, NVLink/NVSwitch, InfiniBand, or RoCE would be highly advantageous.
• Experience across Kubernetes, Slurm, NVIDIA GPU Operator, NCCL, RDMA / GPUDirect, high-performance storage, GPU cluster networking, HLD / LLD production, and technical pre-sales/customer-facing architecture is desirable.

Responsibilities:

• We design large-scale GPU and AI infrastructure for enterprise customers.
• We develop technical architecture, system designs, and infrastructure proposals.
• We create detailed HLDs, LLDs, and Bills of Materials.
• We design GPU cluster architectures around NVIDIA platforms.
• We work with NVLink, NVSwitch, InfiniBand, and RoCE.
• We design high-performance networking and storage environments.
• We support both bare-metal and Kubernetes-based deployments.
• We work with technologies such as Slurm, Kubernetes, NVIDIA GPU Operator, and NCCL.
• We support technical sales opportunities and major customer engagements.
• We run technical workshops with senior customer stakeholders.
• We support RFP/RFI responses and complex technical proposals.
• We help design and validate Proof-of-Concept environments.
• We troubleshoot performance across GPU, networking, and storage infrastructure.
• We work closely with engineering teams, customers, and technology partners.

Technologies:

• AI
• Cloud
• InfiniBand
• Support
• Kubernetes
• Machine Learning
• RDMA

More:

We are an exciting and rapidly growing technology business operating in AI, GPU, HPC, and data centre infrastructure. This is a senior technical role for someone who wants to be both hands-on and customer-facing, working on cutting-edge AI infrastructure rather than traditional cloud or data centre projects. The position is remote or hybrid, initially part-time with the potential to move to full-time, with an immediate start available.

last updated 33 week of 2026