AI & HPC Infrastructure Engineer
Core
Design, build, and operate advanced AI infrastructure and accelerated computing solutions (GPU/DPU/LPU clusters) for enterprise clients, enabling large-scale model training, inference, and agentic AI workflows.
Role type
Senior Infrastructure Engineer (AI & HPC)
Builds
Scalable AI infrastructure services including Bare-Metal-aaS, GPUaaS, AIaaS, and agentic AI frameworks for enterprise clients.
Domain
AI Infrastructure, High-Performance Computing (HPC), Cloud & On-Premises Hybrid Environments
Deliverable
production ML models
Required skills
Accelerated computing platforms (GPUs, DPUs, LPUs), Cluster management & orchestration (Kubernetes, Slurm, Run:ai), Infrastructure automation (Terraform, Ansible), AI/LLM inference engines (TensorRT-LLM, vLLM, Triton), Networking (InfiniBand, SONiC), Storage (NVMe, VAST, Weka), Python, NVIDIA tools (BCM, NGC, NCCL)
Preferred skills
MLOps/LLMOps frameworks, API development (REST, OpenAPI), Agentic AI architecture (RAG, tool calling), MCP server integration, Specialty cloud platforms (CoreWeave, Nebius), ML frameworks (PyTorch, TensorFlow)
Technologies
Kubernetes, Slurm, Run:ai, Terraform, Ansible, Python, NVIDIA Base Command Manager, TensorRT-LLM, vLLM, Triton Inference Server, InfiniBand, SONiC, NVMe, CoreWeave, Nebius
Responsibilities
Design and implement AI infrastructure and accelerated computing solutions; Deploy and manage XPU-based clusters across bare-metal and containerized environments; Integrate AI platforms with IT systems and governance controls; Architect agentic AI infrastructure with secure APIs; Build MCP servers for agent monitoring and tuning; Develop architecture diagrams and operational runbooks; Provide technical guidance and optimization for AI workloads.
Seniority
Senior, hands-on IC
