Platform Support Architect

Key Responsibilities:

• Act as the primary NVIDIA AI Enterprise and vector database solutions expert for HyperPOD customer environments, bringing deep knowledge of NVAIE services and vector databases.
• Own complex end-to-end triage across GPU, NVAIE services, vector DB, Kubernetes, Docker, high-speed networking, and Infinia storage.
• Diagnose and resolve performance bottlenecks in RAG and agentic AI workflows, from model selection to vector search.

Required Experience & Skills:

• 5+ years in Linux-based infrastructure roles supporting production systems; strong hands-on with containers and Kubernetes.
• Demonstrated experience operating GPU-accelerated workloads in production, including NVIDIA GPUs, CUDA, and GPU Operator.
• Practical experience with AI storage and networking for HPC/AI clusters, including high-performance storage and RDMA-accelerated networking.

What Success Looks Like:

• Within 6–12 months, become the go-to internal expert for how the AI and networking stack works in production across Support, PS, Product, and NPI.
• Drive speed and quality of support at the solution level through high-quality diagnostics, architecture insight, and well-defined patterns.
• Establish clear, repeatable triage and escalation patterns for AI-side incidents that L1/L2 storage engineers can follow confidently.