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).
Preferred Qualifications
- Experience with BBCM, and DGX BasePOD/SuperPOD configuration
Certifications by Nvidia or equivalent OEM.
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