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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Cloud Infrastructure and DevOps Solutions Architect - **Company:** NVIDIA Corporation - **Location:** Courbevoie, France - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Board Bringup, Artificial Intelligence, Bash Shell, Ubuntu (Operating System), Cloud Computing, Computer Clusters, Configuration Management, Nvidia CUDA, Computer Engineering, Data Centers, Linux, DevOps, Microprocessors, Fault Tolerance, Firmware, General Parallel File Systems, InfiniBand, Python (Programming Language), Networking Basics, Node.Js, Open Source Technology, Remote Direct Memory Access, Red Hat Enterprise Linux, Ansible, Prometheus, Software Deployment, Systems Architecture, Data Logging, Graphics Processing Unit (GPU), High Performance Computing, Delivery Pipeline, Grafana, Hardware Testing, Break Fix, Kubernetes, Infrastructure Automation Frameworks, Storage Technologies, Information Technology, Bare Metal, Slurm, ZFS File System, Terraform, Microservices - **Published:** September 19, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/France-Courbevoie/Senior-Cloud-Infrastructure-and-DevOps-Solutions-Architect_JR2025837 ## About the Role * BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, or equivalent experience. * 8+ years in managing scalable cloud environments and automation engineering roles. * Cloud, HPC & GPU Expertise: Proven understanding of networking fundamentals and data centre architectures, with hands-on experience managing HPC/AI clusters and NVIDIA GPU-accelerated infrastructure-deployment, driver and CUDA toolkit management, optimisation, workload profiling and troubleshooting across CPUs, GPUs and high-speed interconnects. * Kubernetes & AI/ML Workloads: Extensive background with Kubernetes for container orchestration, resource scheduling and scaling in GPU-accelerated and HPC environments, including scheduler internals, batch schedulers such as Slurm, and mixed bare-metal/virtualised (e.g. KubeVirt) multi-tenant estates. * Linux & Storage Systems: Deep knowledge of Linux (RedHat, Ubuntu), OS-level security, and protocols. Experience with storage solutions such as Lustre, GPFS, ZFS, XFS, and emerging Kubernetes storage technologies. * Automation, GitOps & Observability: Proficiency in Python and Bash scripting, configuration management and Infrastructure-as-Code tools (e.g. Ansible, Terraform), GitOps-based cluster lifecycle and upgrade management for large fleets, and observability stacks (Grafana, Loki, Prometheus) for monitoring, logging and building fault-tolerant systems. * Fleet Reliability & Customer Engagement: Demonstrated ability to measure and improve MTBI and job goodput on large GPU clusters-fault detection, drain and remediation workflows, SLO/error-budget definition and post-incident review-combined with a strong consultative background leading architectural reviews and presenting to executive stakeholders. Ways to Stand Out from the Crowd: * Knowledge of CI/CD pipelines and container-based microservices architectures for software deployment and automation. * Experience with the NVIDIA GPU and Network Operators for automated GPU and network resource lifecycle management in Kubernetes, and with NVIDIA Base Command Manager (BCM) for provisioning, managing and monitoring GPU clusters at scale. * Familiarity with GPU health and fleet telemetry tooling-DCGM and XID diagnostics, node-level health agents, and fleet-wide reliability intelligence. * Expertise in AI-native scheduling and inference frameworks on Kubernetes (e.g. KAI, Grove, Dynamo, NVIDIA Cloud Functions). * Background with RDMA-based fabrics (InfiniBand or RoCE) in HPC or AI environments. Exposure to Cumulus Linux, SONiC or Spectrum-X fabrics, DPU/DOCA infrastructure services, and NVLink/NVSwitch partition operations (NMX-C / NMX-M) on NVL72-class systems is a strong plus. ## Description We are looking for someone who combines deep technical expertise with strong consulting and communication skills. This role will engage directly with customers, partners, and cross-functional teams to assess, architect, and guide the implementation of large-scale infrastructure projects. The scope spans system architecture, Kubernetes-based platforms, and automation-serving as both a trusted advisor and a hands-on technical leader. You will sit at the centre of NVIDIA's Cloud Partner (NCP) operating model, covering the full Day 1 to Day 2 lifecycle: taking a GPU cluster from hardware handover, through full-solution validation, to a production-stable platform running at maximum goodput. NCP estates are open-source-first and heterogeneous-upstream Kubernetes, KubeVirt, Slurm, Prometheus/Grafana, Cumulus/SONiC and a long tail of ISV software-so this role is deliberately tool-agnostic: you will meet each partner on the stack they actually run rather than on a single proprietary product. What You'll Be Doing: * Own full-solution validation on the partner software stack-the layer above hardware validation-including cluster-wide stability testing, real training-workload acceptance, and multi-day, multi-rack burn-in against agreed MTBI and goodput targets. * Minimise the time from cluster handover to first production workload, working across hardware bring-up, managed-service intake and the partner's own operations teams to remove duplicated validation and handover friction. * Own Day 2 production stability at fleet scale: monitoring, logging and workload orchestration, fault detection and remediation, preventive maintenance, and proactive firmware and field-notice rollout campaigns. * Assess customer environments and operate heterogeneous open platforms-upstream Kubernetes, KubeVirt, Slurm and GPU-aware schedulers-integrated with enterprise-grade networking and storage, and enable third-party ISV workloads on top of them. * Provide consultative guidance and hands-on troubleshooting across the full stack-bare metal, operating system, software stack, container platform, networking and storage-and support R&D, POCs and POVs validating new features, architectures and upgrade approaches. * Act as the technical leader for assigned accounts: run structured knowledge transfer and enablement, and produce runbooks, onboarding materials and best-practice guides so partner teams can operate advanced configurations independently. ## Related Videos - [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes) - [A Deep Dive on How To Leverage the NVIDIA GB200 for Ultra-Fast Training and Inference on Kubernetes](https://www.wearedevelopers.com/videos/1625-a-deep-dive-on-how-to-leverage-the-nvidia-gb200-for-ultra-fast-training-and-inference-on-kubernetes) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [#90DaysOfDevOps - The DevOps Learning Journey](https://www.wearedevelopers.com/videos/548-90daysofdevops-the-devops-learning-journey) - [Docker exec without Docker](https://www.wearedevelopers.com/videos/1094-docker-exec-without-docker) ## Related Articles - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Got AI ideas but no money? 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