Senior Solution Engineer, GPU & AI Infrastructure

Hamilton Barnes ?

United Kingdom

On-site

GBP 90,000 - 140,000

Full time

2 days ago
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Benefits offered by this job

Four-day workweek
Uncapped holidays
Fully remote

Job summary

Unknown Company is a high-performance neocloud provider focused on AI, HPC and cloud-native infrastructure. We are seeking a Senior Solution Engineer to architect GPU clusters for large-scale training and inference using NVIDIA Blackwell platforms.

This remote role offers a four-day work week, uncapped holiday and flexible hours, with direct engagement to CTOs and ML leads. You will produce design documentation, BOMs, and oversee PoC deployments, collaborating with sales and engineering to win

Qualifications

  • 5+ years in Solution Architecture, Systems Engineering or Technical Pre-Sales in HPC/AI infra
  • Deep hands-on knowledge of NVIDIA HGX/DGX platforms, NVLink/NVSwitch, Blackwell architectures
  • Expert-level InfiniBand and RoCE/RoCEv2, plus Kubernetes orchestration and bare-metal tooling
  • Strong technical leadership and fluent English

Responsibilities

  • Author comprehensive High-Level and Low-Level Design documentation for enterprise-scale GPU supercomputing clusters
  • Produce detailed Bills of Materials covering compute nodes, NVLink switches, network fabrics, cabling, cooling, power distribution and high-performance storage
  • Architect scale-up and scale-out topologies for NVIDIA Blackwell B300 and GB300NVL platforms
  • Design high-throughput, low-latency fabrics using InfiniBand and RoCE/RoCEv2 with lossless Ethernet mechanisms
  • Act as technical lead alongside sales on high-value AI infra opportunities, engaging with CTOs and ML leads
  • Architect and oversee PoC deployments, benchmarking with NCCL tests, GPUDirect RDMA and MLPerf

Job description

A high-performance neocloud provider, purpose-built for AI, HPC and cloud-native infrastructure, is looking for a Senior Solution Engineer to act as the primary technical architect on its largest AI and HPC customer engagements. This is a hands-on, customer-facing role designing state-of-the-art NVIDIA GPU clusters for training and inferencing foundation models at scale, spanning bare-metal and Kubernetes-based orchestration on the latest NVIDIA Blackwell architecture. The successful candidate will sit at the intersection of customer business need and ultra-high-performance hardware execution, owning designs from whiteboard to Bill of Materials.

You'll be architecting infrastructure for some of the largest GPU cluster deployments serving major global AI labs, working directly on the bleeding edge of NVIDIA Blackwell (B300, GB300NVL) rather than legacy hyperscaler stacks.

The business is scaling fast as a genuine alternative to the traditional hyperscalers, stripping out legacy cloud overhead to deliver bare-metal GPU performance and predictable pricing, and this role sits right at the centre of that growth story.

Fully remote with no fixed office, a four-day working week as standard, uncapped holiday and no set hours: this is flexible, autonomous working built around output rather than presenteeism.

Responsibilities:

Author comprehensive High-Level and Low-Level Design documentation for enterprise-scale GPU supercomputing clusters

Produce detailed Bills of Materials covering compute nodes, NVLink switches, network fabrics, cabling, cooling, power distribution and high-performance storage

Architect scale-up and scale-out topologies (NVLink/NVSwitch, Fat-Tree, Rail-Optimised) for NVIDIA Blackwell B300 and GB300NVL platforms

Design high-throughput, low-latency fabrics using InfiniBand and RoCE/RoCEv2, including lossless Ethernet mechanisms such as PFC, ECN and Adaptive Routing

Act as technical lead alongside sales and commercial teams on high-value AI infrastructure opportunities, engaging directly with customer CTOs, Chief AI Officers and ML engineering leads

Architect and oversee proof-of-concept deployments, benchmarking with tools such as NCCL tests, GPUDirect RDMA and MLPerf to validate real-world workload performance

Experience Required (NOT ALL ESSENTIAL):

Experience: 5+ years in Solution Architecture, Systems Engineering or Technical Pre-Sales, focused on high-performance cloud, HPC or AI infrastructure

Core Tech/Domain: Deep hands-on knowledge of NVIDIA HGX/DGX platforms, NVLink/NVSwitch fabrics and Blackwell architectures (B300, GB300NVL, GB200 NVL72/NVL36)

Methodology/Protocols: Expert-level InfiniBand (Quantum-2/Quantum-X800, Adaptive Routing) and RoCE/RoCEv2 (Spectrum-X/Spectrum-4), plus Kubernetes orchestration (NVIDIA GPU Operator, MPI Operator) and bare-metal tooling (Slurm, Ansible, Terraform)

Soft Skills: Strong technical leadership and presentation skills, able to translate complex hardware and network trade-offs for executive stakeholders; strong spoken and written English is essential

Four-day working week as standard (five-day only when attending events)

Uncapped holiday

Fully remote, flexible working with no fixed hours

Direct exposure to some of the largest GPU cluster deployments for major global AI labs

Collaborative, inclusive culture with genuine autonomy

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