AI Platform Consultant (NetApp AI Pod – On-Prem)

ESRhealthcare • Phoenix, AZ

7d • Onsite

About The Position

Our client is deploying a NetApp AI Pod–based platform to support LLM applications (RAG/Agents) and GPU-based training/inference in an on-premise environment. We are seeking an experienced AI Platform Consultant with deep expertise in non-Microsoft-first AI development, enterprise AI integration, and GPU-optimized infrastructure. This role will lead a 4–6 week discovery and pilot phase, followed by implementation and production hardening of an AI platform designed to operate in regulated and security-sensitive environments.

Requirements

• 7+ years of experience in AI/ML solution design and deployment, preferably in on-premises or hybrid cloud environments.
• Strong expertise in LLM-based applications (RAG, agents, fine-tuning, inference pipelines).
• Hands-on experience with GPU infrastructure (NVIDIA, CUDA, TensorRT).
• Familiarity with NetApp AI Pod or similar storage/compute AI reference architectures.
• Strong background with non-Microsoft AI ecosystems (Hugging Face, PyTorch, TensorFlow, LangChain, Kubernetes-based MLOps, etc.).
• Experience delivering AI projects for regulated industries (public sector, healthcare, finance, or defense).
• Excellent communication and stakeholder management skills.

Nice To Haves

• Prior experience with government or public sector AI initiatives.
• Familiarity with security/compliance frameworks (FedRAMP, DoD SRG, NIST, HIPAA, CJIS).
• Enterprise consulting background with proven client references.
• Clearance: Active DoD, CJIS, or equivalent preferred.

Responsibilities

• Lead a discovery phase to assess client use cases, data readiness, and AI platform requirements.
• Design and implement on-premises AI solutions leveraging NetApp AI Pod for LLM applications, Retrieval-Augmented Generation (RAG), and inference pipelines.
• Configure and optimize GPU environments for training and inference workloads.
• Build and validate AI/ML pipelines, ensuring scalability, resilience, and compliance with government/regulatory standards.
• Collaborate with infrastructure and security teams to integrate AI systems with existing enterprise environments.
• Provide documentation, knowledge transfer, and a Statement of Work (SOW) deliverable outlining scope, milestones, and transition plan.
• Support production hardening and performance tuning post-pilot.

What This Job Offers

• Career Level: Mid Level
• Education Level: No Education Listed