Sr. AI Engineer

Peter Millar

$120K — $145K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in ML/AI engineering with experience in production generative-AI delivery such as RAG and personalization.
  • Proficiency in Microsoft Foundry (Azure AI Foundry) and Azure AI services, including LLM/RAG architectures.
  • Experience with Model Context Protocol (MCP) and prompt engineering.
  • Familiarity with Microsoft Fabric and One Lake for data management in AI applications.
  • Strong skills in Python and MLOps including CI/CD, monitoring, and cost management.

Responsibilities

  • Build and deploy AI features including search, personalization, and content generation on Microsoft Foundry.
  • Implement LLM and RAG solutions, connecting models to governed data using MCP.
  • Develop and tune prompts, retrieval strategies, and workflows using the Foundry Agent Service.
  • Establish MLOps deployment, monitoring, evaluation, and cost-management practices for AI projects.
  • Implement continuous integration and deployment for AI artifacts and automated evaluation.
  • Work with data engineering to ensure data readiness for AI applications.
  • Document responsible AI practices and ensure compliance with company policies.

Benefits

  • Opportunity to work with a dynamic team focused on internal AI capabilities rather than reliance on external consultants.
  • Engagement in cutting-edge projects utilizing Microsoft Azure AI technologies.
  • Mentorship opportunities allowing for professional growth and development in the AI/ML field.
  • Collaborative work environment partnering with data science and engineering teams.
Full Job Description
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.

ESSENTIAL FUNCTIONS:

Production of AI Capability
  • 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.

MLOps Foundation
  • 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.

Risk Management & Guardrails
  • 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.

Collaboration & Mentorship
  • 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.


TECHNICAL COMPETENCIES (REQUIRED):
  • 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.


DESIRED EDUCATION AND EXPERIENCE:
  • 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.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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