AI & HPC Infrastructure Engineer

Responsibilities: Design and implement AI infrastructure and accelerated computing solutions aligned to performance, scalability, resiliency, and governance. Deploy, configure, and manage XPU-based clusters (GPU, DPU, LPU, CPU) across bare-metal and containerized environments using Slurm, Run:ai, Kubernetes, and container platforms to deliver services (Bare-Metal-aaS, GPUaaS, AIaaS, Token-aaS, model serving, agentic AI frameworks). Integrate AI infrastructure platforms with existing IT systems, data pipelines, security, model-serving endpoints, and governance controls. Design and implement agentic AI infrastructure with service integration, endpoints, tool/function calling, retrieval patterns, and workflow orchestration with secure APIs and policy controls. Build and integrate MCP servers, tools, connectors, and adapters enabling agents to monitor, troubleshoot, and tune infrastructure for high availability and low latency networking. Architect and deploy with NVIDIA tools (Base Command Manager, NGC, NCCL, NVLink, CUDA) and LLM inference engines (TensorRT-LLM), production serving (vLLM, SGLang), orchestration (Triton, NVIDIA Dynamo, llm-d), and benchmarks (MLPerf, fio, iperf). Develop and maintain architecture diagrams, baselines, and runbooks. Provide guidance, troubleshooting, and optimization across AI workloads including large-scale training, inference, simulations, and agentic pipelines, leveraging digital twins for validation and cost optimization. Travel may be required (25% to 100% depending on business needs).

Key requirements: 5+ years designing, deploying, and managing AI infrastructure across on-prem, cloud, and hybrid environments for large enterprises and hyperscalers (experience with multiple industry clients). 5+ years hands-on experience with accelerated computing platforms (GPUs/DPUs/LPUs/CPUs), high-speed interconnects, data center networking, and AI storage architectures. 5+ years experience with cluster management, workload scheduling, orchestration, observability, and automation using Kubernetes, Slurm, Run:ai, AWS, Azure, GCP, VMware, Nutanix, Python, Terraform, Ansible. Bachelor's degree or equivalent (minimum 12 years) work experience; Associate's degree requires minimum 6 years work experience. Troubleshooting Optimization Cross-functional collaboration Kubernetes Slurm Run:ai