Senior Solutions Engineer GPU Infrastructure - Systems Integrator

Keen to join a company that champions growth and development?

Join a sovereign cloud and AI platform that combines the openness of public cloud with the security and control of private environments, making the cloud easier to use, faster to deploy, and fairer to pay for. Offering public cloud, private cloud, and high-performance GPU infrastructure with clear, predictable pricing, it helps organisations innovate while keeping control of their data, infrastructure, and spend.

The organization is inviting applications from experienced professionals for the role of Lead Technical Architect on large-scale AI and HPC customer engagements. The ideal candidate will design GPU supercomputing clusters for training and inferencing foundation models, turning customer ambitions into production-ready designs from the first workshop through to proof-of-concept sign-off. The role includes a 4-day working week and remote flexibility.

Ready to take your expertise to the next level? Get in touch today!

Responsibilities

• Author enterprise-grade High-Level and Low-Level Design documentation for large-scale GPU clusters, with peer-reviewed designs delivered within deal timelines
• Produce detailed Bills of Materials covering compute, NVLink switching, fabrics, optics and cabling, liquid and air cooling, power distribution and parallel storage
• Architect scale-up (NVLink/NVSwitch) and scale-out (Fat-Tree, Rail-Optimised) topologies across InfiniBand (NDR/X800) and RoCEv2 (Spectrum-X) with lossless Ethernet tuning (PFC, ECN, Adaptive Routing)
• Deliver tailored bare-metal (Slurm, OpenMPI) and cloud-native (Kubernetes, GPU Operator, Network Operator, Run:ai, Kubeflow) multi-tenant architectures, integrated with GPUDirect Storage and high-performance file systems such as VAST Data
• Act as technical lead alongside sales: run architecture workshops with CTOs, Chief AI Officers and ML engineers, and own technical responses to complex RFPs and RFIs
• Design and oversee PoCs, benchmarking with NCCL tests, GPUDirect RDMA, MLPerf and Megatron-LM, and resolving congestion, routing and thermal/power challenges, while feeding market and hardware insight back to product and platform engineering

Skills/Must have

• Experience: 5+ years in Solutions Architecture, Systems Engineering or Technical Pre-Sales within high-performance cloud, HPC or AI infrastructure
• Core Tech/Domain: Deep hands-on knowledge of NVIDIA HGX/DGX and Blackwell platforms (B300, GB300 NVL, GB200 NVL72/36); expert-level InfiniBand (Quantum-2/X800, subnet management) and RoCE/RoCEv2 (Spectrum-X/Spectrum-4); GPUDirect RDMA and Storage
• Methodology/Protocols: Kubernetes (CNI, GPU Operator, RDMA Shared Device Plugin, MPI Operator) and bare-metal (Slurm, Ansible, Terraform, PyTorch/NCCL tuning); proven HLD, LLD, rack diagram and BOM authorship; awareness of liquid cooling (direct-to-chip, CDU) and 100kW+ per rack power constraints
• Soft Skills: Credible technical leadership and presentation presence at executive level; able to explain complex network and hardware trade-offs clearly; a diagnostic mindset for hardware-software bottlenecks in distributed training and inference. Must be UK based

Desirable Skills

• NVIDIA Certified Professional: AI Infrastructure (NCP-AII)
• NVIDIA Certified Professional: AI Networking (NCP-AIN)
• NVIDIA Certified Professional: InfiniBand (NCP-IB)
• NVIDIA Certified Associate / Professional: AI Workload Deployment & Cloud Native
• Degree in Computer Science, Electrical or Systems Engineering (or equivalent practical experience)

Benefits

• 4-day working week (excluding event attendance)
• Uncapped holiday
• Remote-first working with flexibility and autonomy
• Competitive benefits package
• Inclusive, collaborative culture

Salary

• £140,000 - £160,000