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Senior Solution Engineer – GPU & AI Infrastructure

Job in Bristol, Bristol County, BS1, England, UK
Listing for: Civo Ltd
Full Time position
Listed on 2026-08-16
Job specializations:
  • IT/Tech
    Systems Engineer, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below

Senior Solution Engineer – GPU & AI Infrastructure

About Civo:

Civo is a high-performance neocloud provider purpose-built for the demands of modern AI, high-performance computing (HPC), and cloud-native infrastructure. We eliminate legacy cloud overhead to deliver ultra-low-latency compute, bare-metal GPU performance, and streamlined Kubernetes orchestration at scale.

Purpose-designed for AI engineering teams, enterprises, and research institutions, Civo delivers direct access to cutting-edge NVIDIA GPU clusters, high-speed fabrics, and parallel storage systems required to train, fine-tune, and deploy foundation models efficiently. We combine high-density infrastructure with predictable pricing and maximum compute throughput, empowering organizations to scale AI workloads without the complexity or cost bloat of traditional hyperscalers.

About the Role:

As a Senior Solution Engineer – GPU & AI Infrastructure, you will serve as the primary technical architect for Civo’s large-scale AI and high-performance computing (HPC) customer initiatives. You will be responsible for designing state-of-the-art NVIDIA GPU clusters tailored for training and inferencing massive foundation models.

In this role, you will bridge the gap between customer business objectives and ultra-high-performance hardware execution. You will lead technical engagements, translate complex AI workload requirements into production-ready High-Level Designs (HLD), Low-Level Designs (LLD), and detailed Bills of Materials (BOM). Your expertise will span bare-metal and Kubernetes-based orchestrations across cutting-edge NVIDIA Blackwell architectures (e.g., B300 and GB300NV
L) using ultra-low-latency Infini Band and high-speed RoCE networking fabrics.

Responsibilities:

Solution Design & Architecture

  • System Design Documents:
    Author comprehensive High-Level Design (HLD) and Low-Level Design (LLD) documentation for enterprise-scale GPU supercomputing clusters.
  • Bill of Materials (BOM):
    Generate detailed BOMs covering compute nodes, NVLink switches, network fabrics, transceivers/cabling, liquid/air cooling requirements, power distribution, and high-performance storage.
  • GPU Cluster Topology:
    Architect scale-up (NVLink/NVSwitch) and scale-out network topologies (Fat-Tree, Rail-Optimized) for NVIDIA Blackwell platforms, specifically B300 and GB300NV
    L rack-scale architectures.
  • Fabric & Networking Engineering:
    Design high-throughput, low-latency networking architectures utilizing both Infini Band (e.g., NDR/X800) and RoCE / RoCEv2 (e.g., NVIDIA Spectrum-X / Spectrum-4) with lossless Ethernet mechanisms (PFC, ECN, Adaptive Routing).
  • Multi-Tenant & Deployment Models:
    Deliver tailored architectures for both Bare-Metal (Slurm, OpenMPI, bare-metal provisioning) and Cloud-Native / Kubernetes environments (NVIDIA GPU Operator, Network Operator, Run:ai, Kube Flow).
  • Storage Integration:
    Architect high-bandwidth parallel storage solutions utilizing GPUDirect Storage (GDS) and enterprise AI file systems (e.g., VAST Data).

Technical Sales Support & Customer Engagement

  • Partner with Civo’s sales and commercial teams as the technical lead for high-value AI infrastructure opportunities.
  • Engage directly with customer CTOs, Chief AI Officers, infrastructure leads, and ML engineers to evaluate technical requirements, compute sizing, and fabric choices.
  • Lead deep-dive architectural workshops and technical presentations on Civo's bare-metal GPU and managed Kubernetes offerings.
  • Produce precise technical proposals and lead responses to complex RFPs/RFIs regarding AI infrastructure.

Proof-of-Concept (PoC) & Benchmarking

  • Architect and oversee Proof-of-Concept (PoC) deployments to validate real-world performance for customer workloads.
  • Benchmark cluster performance using industry-standard tools (NCCL tests, GPUDirect RDMA latency/bandwidth, MLPerf, Megatron-LM benchmarks).
  • Address network congestion, fabric routing, and thermal/power optimization during validation phases.

Product & Ecosystem Collaboration

  • Serve as the bridge between enterprise AI clients, hardware vendors (NVIDIA, network OEMs), and Civo’s internal platform engineering team.
  • Provide continuous feedback to product teams on…
Position Requirements
10+ Years work experience
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