Senior Solution Engineer – GPU & AI Infrastructure
Civo ·
- Seniority
- Senior
- Category
- Solutions engineering
- Experience
- 5+ years
Civo ·
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 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.