Senior Solution Engineer – GPU & AI Infrastructure

Schedule: 4-day week, 32 hours a week

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.

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 GB300NVL) using ultra-low-latency InfiniBand and high-speed RoCE networking fabrics.

• 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 GB300NVL rack-scale architectures.

• Fabric & Networking Engineering: Design high-throughput, low-latency networking architectures utilizing both InfiniBand (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, KubeFlow).

• Storage Integration: Architect high-bandwidth parallel storage solutions utilizing GPUDirect Storage (GDS) and enterprise AI file systems (e.g., VAST Data).

• 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.

• 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.

• 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 market trends, hardware platform demands, and feature requirements for AI/GPU orchestration.

• Technical Wins: Achieve high technical win rates on large-scale AI/GPU cluster sales opportunities.

• Design Excellence: Successfully deliver complete, peer-reviewed HLDs, LLDs, and BOMs within target deal timelines.

• Customer Satisfaction: Achieve successful PoC completion and sign-off for enterprise clients scaling AI workloads on Civo infrastructure.

• 5+ years in a Solution Architecture, Systems Engineering, or Technical Pre-Sales role focused on high-performance cloud, HPC, or AI infrastructure.

• Bachelor’s degree in Computer Science, Electrical Engineering, Systems Engineering, or equivalent practical experience.

• NVIDIA GPU Architecture: Deep hands-on knowledge of NVIDIA HGX/DGX platforms, NVLink/NVSwitch fabrics, and Blackwell architectures (B300, GB300NVL, GB200 NVL72/NVL36).

• High-Speed Networking: Expert-level knowledge of cluster fabric topologies:

• InfiniBand: Quantum-2 / Quantum-X800, Subnet Management, Adaptive Routing.

• RoCE / RoCEv2: Spectrum-X / Spectrum-4 Ethernet switches, PFC, ECN, RoCE configuration, and optimization.

• GPU Direct Technologies: GPUDirect RDMA (GDR) and GPUDirect Storage (GDS).
• Orchestration & Platforms: Proficiency in deploying and optimizing GPU workloads on:

• Kubernetes: Container networking (CNI), NVIDIA GPU Operator, RDMA Shared Device Plugin, MPI Operator.

• Bare-Metal: Slurm, Ansible, Terraform, PyTorch/NCCL environment tuning.
• Documentation Skills: Demonstrated experience creating enterprise-grade HLDs, LLDs, network rack diagrams, and itemized BOMs.

• Power & Thermal Awareness: Familiarity with high-density datacenter environments, liquid cooling technologies (Direct-to-Chip, CDU/liquid loop setups), and power delivery constraints for 100kW+ per rack deployments.

• Strong technical leadership and presentation skills, with the ability to articulate complex network and hardware tradeoffs to executive stakeholders.

• Problem-solving mindset capable of diagnosing complex hardware-software interaction bottlenecks in distributed training/inference setups.

• Must be UK based.

• 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.

Why Join Civo?

• Competitive compensation and benefits package.

• 4-day week company (unless attending an event).

• Uncapped holiday.

• Remote work environment with flexibility and autonomy.

• Collaborative and inclusive culture that values diversity and creativity.

• Opportunity to work with a dynamic and innovative team in the fast-growing cloud industry.