Solution Architect – GPU, HPC

Job not on LinkedIn

🕒 July 21

🇬🇧 United Kingdom – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 21%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NexGen Cloud

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

💼 Consulting

📦 Logistics

🏭 Manufacturing

Consulting • Logistics • Manufacturing

NexGen Cloud is a provider of large-scale, sovereign and sustainable AI cloud infrastructure and GPU-as-a-service. It offers the AI Supercloud and Hyperstack platforms with on-demand NVIDIA HGX/H100/GB200 GPUs, managed Kubernetes, custom hardware/software configurations, and consulting and R&D partnerships through NexGen Labs to support enterprise training of foundational models and GenAI workloads. The company focuses on scalable, hybrid and sovereign deployments in Europe and North America and provides POCs, onboarding, and ongoing support.

📋 Description

• Own the technical sales cycle end-to-end from initial customer brief through architecture design, proposal, and delivery handover • Act as the primary technical authority for GPU cloud solution design • Engage directly with prospective and existing customers to understand workload requirements, technical constraints, and commercial objectives • Produce detailed solution designs including architecture diagrams, network topology, storage configurations, and GPU resource allocation models • Collaborate with Pre-Sales Engineering, Data Centre, Infrastructure, and Network Engineering teams to validate delivery feasibility • Build and maintain reference architectures and solution templates for AI/ML training, inference, HPC, and rendering workloads • Develop technical proposals, RFP responses, and statements of work • Support commercial discussions with clear scoping, realistic estimates, and risk assessments • Define and maintain comprehensive Bills of Materials for proposed solutions • Feed recurring customer requirements and competitive intelligence to engineering leadership to influence the Hyperstack product roadmap

🎯 Requirements

• Proven experience in HPC or AI software stack design and delivery at scale, including workload profiling, scheduler configuration (SLURM, PBS, or equivalent), MPI/NCCL tuning, and distributed training frameworks such as PyTorch, JAX, or DeepSpeed • Deep understanding of GPU software environments: CUDA, cuDNN, NCCL, driver stacks, and tooling for large-scale AI training and inference workloads • Hands-on experience optimising AI and HPC workloads across multi-GPU and multi-node configurations, including profiling, bottleneck identification, and performance tuning • Strong working knowledge of Docker, Kubernetes, NVIDIA GPU Operator, and container-native workload management • Background in an OEM, hyperscaler, neo-cloud, or enterprise/research HPC environment • Demonstrable exposure to the full design-to-deployment lifecycle for GPU-accelerated workloads • Ability to produce clear, professional technical documentation and architecture diagrams • Ability to engage confidently with customers, vendors, and internal engineering teams as a technical authority • Experience with large-scale cluster performance benchmarking, NCCL tests, MLPerf, or equivalent • Exposure to MLOps tooling and AI platform layers such as MLflow, W&B, Triton, vLLM, Kubeflow, and Airflow • Familiarity with InfiniBand and high-performance networking • Commercial awareness and experience contributing to BoMs, technical proposals, or RFP responses

🏖️ Benefits

• Competitive salary and annual discretionary bonus scheme • Employee wellbeing benefits • 25 days of holiday, plus public holidays • Flexible working arrangements • Real ownership and autonomy • The chance to work at the cutting edge of GPU cloud infrastructure • Clear career progression and growth opportunities • A collaborative, international culture built on trust, transparency, and ownership • The opportunity to shape how NexGen Cloud is positioned and perceived in a competitive and fast-moving market