Senior Solution Engineer – GPU & AI Infrastructure

About Civo:

Civo is revolutionising the cloud industry by providing developers and businesses with cutting-edge, developer-friendly cloud solutions. With a focus on simplicity, performance, and reliability, Civo enables its clients to unleash the full potential of their projects and scale with ease. As a company committed to excellence and innovation, Civo values diversity, collaboration, and continuous improvement.

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 act as the critical technical bridge partnering with the Sales team across both pre-sales discovery and post-sales implementation phases.

During the pre-sales cycle, you will bridge the gap between customer business objectives and ultra-high-performance hardware execution by translating complex AI workload requirements into production-ready High-Level Designs (HLD), Low-Level Designs (LLD), and detailed Bills of Materials (BOM). Post-sales, you will guide customers through successful deployments, ensuring that the architectures you designed are effectively operationalized on Civo’s platform.

Your expertise will span bare-metal and Kubernetes-based orchestrations across cutting-edge NVIDIA architectures (including the Blackwell platform) using ultra-low-latency InfiniBand and high-speed RoCE networking fabrics.

Responsibilities:

Pre-Sales: Solution Design & Architecture

• System Design Documents: Author comprehensive High-Level Design (HLD) and Low-Level Design (LLD) documentation for enterprise-scale GPU supercomputing clusters based on customer requirements.

• 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 advanced NVIDIA platforms.

• Fabric & Networking Engineering: Design high-throughput, low-latency networking architectures utilizing InfiniBand and RoCE / RoCEv2 with lossless Ethernet mechanisms (PFC, ECN, Adaptive Routing).

• Multi-Tenant & Deployment Models: Deliver tailored architectures for both Bare-Metal (Slurm, OpenMPI) and Cloud-Native / Kubernetes environments (NVIDIA GPU Operator, Network Operator, KubeFlow).

• Technical Proposals: Produce precise technical proposals and lead technical responses to complex RFPs/RFIs regarding AI infrastructure.

Pre-Sales & Post-Sales: Customer Engagement & Validation

• Sales Partnership: Act as the primary technical partner to the commercial team, utilizing structured engagement frameworks (e.g., MEDDPIC) to drive high-value AI infrastructure opportunities.

• Executive Consultation: Engage directly with customer CTOs, Chief AI Officers, infrastructure leads, and ML engineers to evaluate technical requirements, compute sizing, and fabric choices.

• Proof-of-Concept (PoC): Architect and oversee PoC deployments to validate real-world performance for customer workloads prior to full commitment.

• Post-Sales Implementation Guidance: Serve as the technical continuity lead post-sale, ensuring customer workloads successfully transition from the PoC/design phase into production deployment.

• Performance Benchmarking (Post-Sales): Guide the benchmarking of cluster performance during deployment using industry-standard tools (NCCL tests, GPUDirect RDMA latency/bandwidth) and address network or thermal optimization issues during validation.

Product & Ecosystem Collaboration

• Vendor Alignment: Serve as the bridge between enterprise AI clients, hardware vendors (NVIDIA, network OEMs), and Civo's internal platform engineering team.

• Product Feedback Loop: Provide continuous feedback from customer engagements to product teams regarding market trends, hardware platform demands, and feature requirements for AI/GPU orchestration.

Key Results/Objectives:

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

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

• Successful Onboarding: Achieve successful PoC completion and sign-off for enterprise clients, and maintain technical oversight through initial post-sales deployment.

Requirements:

Experience & Core Qualifications

• 5+ years in a Solution Architecture, Systems Engineering, or Technical Pre/Post-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.

• Demonstrated experience supporting enterprise customers through the full lifecycle of complex technical sales, from initial discovery to deployment execution.

Technical Expertise

• NVIDIA GPU Architecture: Deep hands-on knowledge of NVIDIA HGX/DGX platforms, NVLink/NVSwitch fabrics, and Blackwell architectures.

• High-Speed Networking: Expert-level knowledge of cluster fabric topologies across InfiniBand (Quantum/Subnet Management) and RoCE / RoCEv2 (Spectrum Ethernet, PFC, ECN).

• GPU Direct Technologies: Familiarity with GPUDirect RDMA (GDR) and GPUDirect Storage (GDS).

• Orchestration & Platforms: Proficiency in deploying and optimizing GPU workloads on Kubernetes (CNI, NVIDIA GPU Operator) and Bare-Metal (Slurm, PyTorch/NCCL 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 and liquid cooling technologies.

Soft Skills

• 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.

Nice to Have:

• 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 work 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.