Senior AI Engineer — Production GenAI & MLOps Leader

Peter Millar; Milwaukee (WI); On-site; USD 140,000 - 190,000; Full time

Job summary

Peter Millar seeks a Senior AI/ML Engineer to advance internal AI capabilities, integrating ML engineering, GenAI, and prompt engineering on Microsoft Foundry (Azure AI Foundry). Build, deploy, and monitor production AI features, driving scalable AI across search, personalization, and internal copilots.

Ideal candidates have 5+ years in ML/AI engineering with hands-on Foundry/Azure AI Foundry experience, MCP/RAG/LLM expertise, and strong Python/MLOps fundamentals to partner across data teams and

Qualifications

• 5+ years in ML/AI engineering with production delivery.
• Hands-on Microsoft Foundry/Azure AI Foundry experience.
• Experience MCP, RAG, and LLM integration; strong prompt engineering.
• Familiarity with Microsoft Fabric/One Lake.
• Strong Python; solid MLOps fundamentals.

Responsibilities

• Build and deploy production AI features; search, personalization, content generation, and internal copilots on Microsoft Foundry (Azure AI Foundry).
• Implement LLM and RAG solutions grounded in governed One Lake data, using MCP to connect models to data and tools.
• Develop and tune prompts, retrieval strategies, and agent workflows via the Foundry Agent Service and model catalog.

Skills

Foundry/Azure Foundry

Azure OpenAI / LLM

MCP (Model Context Protocol)

RAG integration

Python

MLOps CI/CD

Fabric/One Lake data

Education

BS/MS in CS/ML

Azure AI certifications a plus

Tools

Microsoft Foundry

Azure AI Foundry

Fabric & One Lake

Job description

Peter Millar seeks a Senior AI/ML Engineer to advance internal AI capabilities, integrating ML engineering, GenAI, and prompt engineering on Microsoft Foundry (Azure AI Foundry). Build, deploy, and monitor production AI features, driving scalable AI across search, personalization, and internal copilots.

Ideal candidates have 5+ years in ML/AI engineering with hands-on Foundry/Azure AI Foundry experience, MCP/RAG/LLM expertise, and strong Python/MLOps fundamentals to partner across data teams and