Senior Cloud Infrastructure, DevOps Solutions Architect

This is a fully remote position, open to applicants in France, +3 more countries.

📋 Description

• Take ownership of comprehensive validation for partner software stacks, which includes cluster-wide stability testing, acceptance of real training workloads, and multi-day, multi-rack burn-in.

• Reduce the time taken from cluster handover to the initiation of the first production workload by effectively coordinating hardware bring-up, managed-service intake, and partner operations teams.

• Manage Day 2 production stability at scale across fleets, including aspects such as monitoring, logging, workload orchestration, fault detection and remediation, preventive maintenance, and the rollout of firmware and field-notice campaigns.

• Evaluate customer environments and operate diverse open platforms including Kubernetes, KubeVirt, Slurm, and GPU-aware schedulers.

• Integrate enterprise-grade networking and storage solutions while enabling third-party ISV workloads.

• Deliver consultative support and hands-on troubleshooting across various domains including bare metal, operating systems, software stacks, container platforms, networking, and storage.

• Assist R&D initiatives, proofs of concept, and proofs of value by validating new features, architectures, and upgrade strategies.

• Serve as the technical leader for designated accounts.

• Conduct structured knowledge transfer and enablement sessions.

• Create runbooks, onboarding documentation, and best-practice guides for partner teams.

⛳️ Requirements

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, or equivalent experience.

• Over 8 years of experience in managing scalable cloud environments and roles in automation engineering.

• Solid understanding of networking principles and data center architectures.

• Practical experience in managing HPC/AI clusters and NVIDIA GPU-accelerated infrastructure, encompassing deployment, driver and CUDA toolkit management, optimization, workload profiling, and troubleshooting.

• Extensive experience with Kubernetes for container orchestration, resource scheduling, and scaling in GPU-accelerated and HPC settings.

• Familiarity with scheduler internals, batch schedulers like Slurm, and mixed bare-metal/virtualized multi-tenant environments such as KubeVirt.

• In-depth knowledge of Linux, including RedHat and Ubuntu, OS-level security, and network protocols.

• Experience with storage solutions including Lustre, GPFS, ZFS, XFS, and Kubernetes storage technologies.

• Proficient in Python and Bash scripting.

• Knowledge of configuration management and Infrastructure-as-Code tools like Ansible and Terraform.

• Experience with GitOps-based management for cluster lifecycle and upgrades across large fleets.

• Familiarity with observability stacks such as Grafana, Loki, and Prometheus.

• Capability to assess and enhance MTBI and job goodput on extensive GPU clusters.

• Experience with fault detection, drain and remediation workflows, SLO/error-budget definitions, and post-incident reviews.

• Strong consultative background in leading architectural reviews and presenting to executive stakeholders.

• Knowledge of CI/CD pipelines and container-based microservices architectures.

• Experience with NVIDIA GPU and Network Operators, as well as NVIDIA Base Command Manager.

• Familiarity with DCGM, XID diagnostics, node-level health agents, and fleet-wide reliability intelligence.

• Expertise in AI-native scheduling and inference frameworks on Kubernetes, such as KAI, Grove, Dynamo, and NVIDIA Cloud Functions.

• Background with RDMA-based fabrics like InfiniBand or RoCE.

• Exposure to Cumulus Linux, SONiC, Spectrum-X fabrics, DPU/DOCA infrastructure services, and NVLink/NVSwitch partition operations is considered a strong advantage.

🏝️ Benefits

• Work with NVIDIA products and contribute to next-generation AI/HPC systems.

• Gain exposure to large-scale infrastructure projects and advanced GPU/HPC technologies.

• Collaborate with customers, partners, and cross-functional teams.

• Engage in technical leadership, knowledge transfer, and enablement opportunities.