Cognizant
Oct 18, 2025 - Cognizant is hiring a remote Infrastructure/GPU Engineer.
Salary: usd 99,000 - 116,000 per year. Location: USA.
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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Salary: usd 99,000 - 116,000 per year. Location: USA.
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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