Senior Cloud Infrastructure Architect (Kubernetes + GPU Cloud + HPC)

# AI Cloud Infrastructure Consultant (Kubernetes, GPU Cloud, HPC) ## Project Overview We are building a next-generation AI cloud platform for GPU-based training and inference. We're looking for an experienced cloud infrastructure consultant to help design the architecture of the platform and review key technical decisions. This is **not** a Kubernetes administration role. We are looking for someone who has architected or operated large-scale cloud infrastructure, preferably for AI, GPU, or HPC environments. The engagement will focus on architecture, design reviews, and technical guidance while our engineering team handles implementation. --- ## Project Scope We are seeking guidance on designing and reviewing: * GPU cloud architecture * Kubernetes platform architecture * Control plane and data plane design * GPU scheduling and orchestration * Multi-tenant architecture * High-performance networking (Cilium, eBPF, service mesh) * Storage architecture for AI workloads * Infrastructure security and isolation * Monitoring, logging, and observability * Scalability and reliability best practices --- ## Required Experience We're looking for someone with strong experience in several of the following areas: ### Kubernetes * Production Kubernetes * Kubernetes internals * Operators * Helm * Cluster Autoscaler / Karpenter * CNI plugins ### GPU Infrastructure * NVIDIA GPU infrastructure * CUDA * MIG * GPU scheduling * AI inference platforms * Large-scale model serving ### Networking * Cilium * eBPF * Hubble * Service mesh * InfiniBand or RoCE (preferred) ### HPC * Slurm * HPC clusters * Distributed AI training * Multi-node workloads ### Storage * S3-compatible object storage * Ceph, BeeGFS, Lustre, or similar * Kubernetes Persistent Volumes ### Infrastructure * Linux * Terraform * Docker * KVM virtualization * Infrastructure as Code ### Observability * Prometheus * Grafana * Loki * OpenTelemetry --- ## Nice to Have Experience designing infrastructure similar to: * GPU-as-a-Service platforms * AI cloud providers * LLM inference platforms * Distributed training infrastructure * Multi-tenant cloud platforms Experience with platforms such as: * Nebius * CoreWeave * Lambda Cloud * Crusoe * AWS * Google Cloud * Azure * Oracle Cloud --- ## Deliverables Depending on the engagement, deliverables may include: * Architecture reviews * Technical recommendations * Infrastructure diagrams * Design documentation * Best-practice guidance * Review of implementation plans * Regular architecture consultation sessions --- ## Ideal Consultant You have previously helped build or operate production cloud infrastructure at scale and can advise on architectural decisions rather than day-to-day operations. Experience with GPU infrastructure, AI platforms, or HPC environments is highly preferred. --- ## When Applying Please include: * A brief summary of your relevant experience * Similar cloud infrastructure projects you've worked on * Your experience with Kubernetes, GPU infrastructure, or HPC * Any public architecture blogs, GitHub repositories, talks, or technical publications (if available) * Your availability and hourly rate If you've worked on AI cloud platforms, GPU infrastructure, hyperscale cloud services, or similar projects, we'd love to hear about your experience.