Senior Solution Engineer – GPU & AI Infrastructure

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.