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Senior AI Infrastructure & Platform Engineer - Riyadh,KSA

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Role Overview:
We are seeking a highly skilled Senior AI Infrastructure & Platform Engineer to join our client’s team in Riyadh. In this role, you’ll be responsible for building, managing, and optimizing scalable AI infrastructure and compute environments that support high-performance workloads, including GPU-accelerated AI/ML pipelines, cluster scheduling, and orchestration.

Key Responsibilities:
  • Deploy, maintain, and optimize GPU-based compute clusters and infrastructure.
  • Manage and operate GPU orchestration tools and platforms such as:
  • Nvidia Base Command Manager (critical)
  • Nvidia AI Enterprise Suite
  • Nvidia GPU and Network Operators
  • Nvidia NIMs and Blueprints
  • Configure, deploy, and maintain compute workloads using scheduling and orchestration tools including:
  • Slurm (critical)
  • Vanilla Kubernetes
  • Install, configure, and maintain the underlying OS (e.g. Canonical Ubuntu) and supporting system software.
  • Monitor and troubleshoot infrastructure performance, availability, and reliability; ensure high uptime for AI/ML workloads.
  • Work with data scientists, ML engineers, and dev teams to define infrastructure requirements, resource allocation, and deployment workflows.
  • Develop automation scripts, CI/CD pipelines, and best practices for infrastructure provisioning and management.
  • Document architecture, configurations, and operational procedures; enforce security, compliance, and backup policies.
Requirements:
Required Skills & Experience:
  • Proven experience managing GPU-based AI/ML infrastructure and compute clusters.
  • Hands-on experience with:
  • Nvidia Base Command Manager
  • Nvidia AI Enterprise Suite
  • Nvidia GPU/Network Operators, NIMs, Blueprints
  • Strong experience with Slurm and/or Kubernetes orchestration.
  • Solid Linux system administration skills — preferably on Ubuntu or similar distributions.
  • Strong scripting/automation ability (e.g. Bash, Python, or relevant tooling) for provisioning, deployment, and maintenance.
  • Excellent troubleshooting and performance-tuning skills.
  • Experience collaborating with ML/data science teams and integrating infrastructure with their workflows.
  • Strong understanding of networking, security, resource allocation, and cluster management best practices.
Preferred Qualifications:
  • Previous experience working in a high-performance computing (HPC) or AI-focused infrastructure team.
  • Knowledge of containerization, container orchestration, and GPUs in cloud or on-prem environments.
  • Experience with CI/CD, infrastructure-as-code (e.g. Terraform, Ansible), monitoring tools, and logging setups.
  • Familiarity with workload scheduling, job queuing, resource quotas, and GPU-shared environments.

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