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Senior Cloud Infrastructure and DevOps Solutions Architect

NVIDIA· Architect, Solutions
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France, Courbevoie, Hybrid (Germany), Hybrid (UK)Full-timePosted 4w ago

About the role

Senior role in NVIDIA Infrastructure Specialist Team focusing on cloud infrastructure, DevOps, Kubernetes-based platforms, and automation for large-scale GPU-accelerated data center deployments. Combines deep technical expertise with consulting and customer-facing leadership across Day 1–Day 2 lifecycle.

Responsibilities

  • 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.

Qualifications

  • 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: Understanding of networking fundamentals and data centre architectures, hands-on experience with 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 fault-tolerant systems.
  • Fleet Reliability & Customer Engagement: 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 consultative background leading architectural reviews and presenting to executive stakeholders.

Skills

Required:Cloud infrastructure managementKubernetesSlurmLinux system administrationNetworking and data center architectures

Benefits

Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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