Infrastructure/GPU Engineer

Cognizant is seeking a highly skilled hands-on Infrastructure Engineer with proven experience in the physical and technical deployment of AI-ready environments optimized for AI and machine learning workloads. This role focuses on NVIDIA DGX or similar systems, GPU-accelerated compute clusters, high-speed networking, and scalable storage solutions. The ideal candidate will have deep expertise in infrastructure design ,deployment, workload orchestration, and performance optimization in enterprise environments.

This is a remote role in the US. Salary range for this role is between $99,000 and $116,000 depending on skills and qualifications of the candidate. Applications will be accepted till 10/21/2025.

Key Responsibilities

System Design & Deployment

• Help in rightsizing GPU investment 

• Architect and deploy NVIDIA DGX systems and GPU-based compute clusters.

• Design and implement scalable parallel filesystems (e.g., Lustre, BeeGFS, GPFS).

• Integrate high-speed interconnects using InfiniBand, RoCE, and RDMA.

• Collaborate on rack planning and airflow optimization.

  Cluster & Infrastructure Management

  • Configure and manage Slurm Workload Manager for job scheduling.

  • Deploy and maintain cluster orchestration tools

  • Automate provisioning using PXE boot, Terraform, Redfish, and Kubernetes.

  • Perform firmware updates, BIOS/IPMI/BMC configuration, and OS provisioning

  • Knowledge of Run.ai, ClearML or similar platform 

    Networking & Performance Optimization

    • Design and validate network topologies including IPMI, internal/external networks, and InfiniBand fabrics.

    • Optimize RDMA and RoCE configurations for low-latency, high-throughput data transfers.

    • Conduct performance benchmarking using GPU-Burn, NCCL, and NVSM.

      Monitoring & Troubleshooting

      • Implement system health checks and diagnostics across compute, storage, and network layers.

      • Troubleshoot hardware/software issues and ensure reliable infrastructure operation.

        Required Skills & Qualifications

        Technical Expertise

        • Deep understanding of NVIDIA DGX architecture, CUDA, and GPU compute.

        • Strong Linux system administration and shell scripting skills.

        • Experience with Slurm, parallel filesystems, and high-speed networking (InfiniBand/RDMA/RoCE).

        • Familiarity with containerization (Docker), orchestration (Kubernetes), and automation tools (Ansible, Redfish).

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          Preferred Qualifications

          • Experience with BBCM, and DGX BasePOD/SuperPOD configuration

            Certifications by Nvidia or equivalent OEM.