AI use among detectives and criminal investigators is little observed so far. Measured exposure for detectives and criminal investigators: 4% (little observed).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

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

Phoenix, AZ

Contracted

Mid Level

Overview

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.

Key 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.

Required Skills & Qualifications

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.

Preferred Qualifications

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.

Engagement Structure

Phase 1 – Discovery (4–6 weeks): Requirements gathering, architecture design, initial proof-of-concept.

Phase 2 – Pilot (6–10 weeks): Build and validate AI workflows with NetApp AI Pod, including training/inference pipelines.

Phase 3 – Production Hardening: Optimize, secure, and scale solution with documentation and handover to client.