Sr AI/ML Engineer

TEKsystems•Durham, NC

3d•$180,000 - $220,000•Hybrid

About The Position

The Senior AI/ML Engineer helps move AI from consultant-led pilots to a sustainable internal capability by combining ML engineering, GenAI integration, and prompt engineering into one Senior role. Using Microsoft Foundry, formerly Azure AI Foundry, and the broader Azure AI stack—grounded in governed Microsoft Fabric and One Lake data—this role builds, deploys, monitors, and continuously improves production AI features such as search, personalization, content generation, and internal copilots, reducing reliance on high-cost consulting. The role may initially be proven through consulting support and then internalized once the approach is established.

Requirements

5+ years in ML/AI engineering, with production generative-AI delivery (RAG, copilots, search, or personalization).
Hands-on Microsoft Foundry / Azure AI Foundry and Azure AI experience strongly preferred.
Experience with MCP, RAG, and LLM integration; strong prompt-engineering skills.
Familiarity with Microsoft Fabric / One Lake and governed data foundations.
Strong Python; solid MLOps and software-engineering fundamentals.
Bachelor’s or Master’s in Computer Science, Machine Learning, or related field; relevant Azure AI certifications a plus.

Nice To Haves

Microsoft Foundry (Azure AI Foundry) hands-on experience with the model catalog, Foundry Agent Service, evaluation, and deployment.
Azure AI production experience with Azure AI services / Azure OpenAI and LLM/RAG architectures.
MCP, RAG & LLMs demonstrated experience with the Model Context Protocol (MCP), retrieval-augmented generation, and prompt engineering.
Microsoft Fabric & One Lake experience grounding AI on governed Fabric/One Lake data (Lakehouse, Direct Lake, shortcuts).
MLOps CI/CD, monitoring, evaluation, and cost management; strong Python.

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 the Model Context Protocol (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.
Establish deployment, monitoring, evaluation, and cost-management practices around AI projects — recognizing AI products require continual refinement, not set-and-forget delivery.
Implement CI/CD for AI artifacts, prompt/model versioning, and automated evaluation.
Partner with data engineering to keep Fabric/One Lake data AI-ready.
Implement guardrails, prompt-injection defenses, output validation, and PII handling.
Ensure technical controls stay aligned with Richemont’s requirements and policies.
Document responsible-AI practices and model evaluations.
Work under AI Engineering Manager and partner with data science and data engineering on shared infrastructure.
Mentor junior engineers and contribute to the AI/ML specialization pathway.