Lead AI Engineer (GenAI / Applied AI)

It's fun to work in a company where people truly BELIEVE in what they're doing! We're committed to bringing passion and customer focus to the business. Peter Millar was founded in 2001 with a single cashmere sweater offered in 24 colors.

Based in Raleigh and Durham, North Carolina, the American lifestyle brand has grown to include luxury performance sportswear, seasonal resort and country club apparel, sophisticated classics, casually refined tailored clothing and sartorial accessories. We strive to capture timeless style upgraded with signature innovations, in designs that are in tune with modern life. We embrace working hard, being kind and doing right by our customers, aiming to set a higher standard for the apparel industry.

The Lead AI Engineer provides dedicated leadership for AI engineering, sitting between data engineering, data science, and business applications. The role owns the end-to-end lifecycle of AI solutions; from model selection and LLM/RAG integration to deployment, monitoring, and governance. They be responsible for operationalizing AI safely at scale on Microsoft Foundry (formerly Azure AI Foundry) and the broader Azure AI stack, grounded in Peter Millar’s governed Microsoft Fabric and OneLake data.

This person establishes a repeatable framework for delivering AI use cases, introduces MLOps discipline, and over time builds and manages a small team of AI/ML engineers ESSENTIAL FUNCTIONS: AI Platform Ownership (Pilot → Production) Own the AI platform built on Microsoft Foundry (Azure AI Foundry): model-catalog selection (OpenAI, Anthropic, Meta, open and frontier models), prompt configuration, evaluation, and deployment.

Stand up the Foundry Agent Service for production agents, conversation management, tool calling, identity, safety, and observability. Build RAG pipelines grounded in governed OneLake data; establish a repeatable framework for copilots, search, and personalization. Reduce dependency on consultants and avoid fragmented point solutions.

MLOps & Lifecycle Discipline Introduce monitoring, evaluation, retraining, and cost-management practices to prevent model degradation over time. Implement CI/CD for AI artifacts, versioning of prompts and models, and automated evaluation. Partner with data engineering to ensure Microsoft Fabric / OneLake data is AI-ready.

Governance & Risk Mitigation Implement guardrails: PII handling, model evaluation, prompt-injection defense, output validation, and content safety. Ensure alignment with enterprise and Richemont AI policies and compliance requirements. Establish responsible-AI standards and documentation.

Team Leadership & Delivery Act as hiring manager and technical lead for future AI/ML engineers; define the specialization pathway. Translate high-value business problems into production-ready AI solutions with measurable ROI. Maximize ROI on existing Fabric, semantic-layer, and MDM investments — avoiding “data rich, AI poor” outcomes.

TECHNICAL COMPETENCIES (REQUIRED): Microsoft Foundry (Azure AI Foundry) — deep, hands-on experience with the model catalog, Foundry Agent Service, Foundry Tools, evaluation/observability, and deployment. Azure AI — production experience with Azure AI services and Azure OpenAI, LLM/RAG architectures, and prompt engineering. Microsoft Fabric & OneLake — experience grounding AI on governed Fabric/OneLake data (Lakehouse, Direct Lake, shortcuts).

MLOps — strong CI/CD, monitoring, evaluation, and cost management; Python. AI governance — experience implementing PII handling, prompt security, and output validation. DESIRED EDUCATION AND EXPERIENCE: 8+ years in ML/AI engineering, including 2+ years leading or managing engineers (or strong technical-lead experience).

Proven delivery of production generative-AI solutions (RAG, copilots, agents) at enterprise scale. Hands-on Microsoft Foundry / Azure AI Foundry experience strongly preferred. Familiarity with Microsoft Fabric / OneLake and governed data foundations.

Bachelor’s or Master’s in Computer Science, Machine Learning, or a 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! Peter Millar & G/FORE are equal opportunity employers.

In accordance with anti-discrimination law, it is the purpose of this policy to effectuate these principles and mandates. Both Peter Millar & G/FORE prohibit discrimination and harassment of any type and they afford equal employment opportunities to employees and applicants without regard to race, color, religion, gender, age, national origin, genetic information, marital status, disability status, protected veteran status, sexual orientation, or any other characteristic protected by law.

Both Peter Millar & G/FORE comply with applicable state, county and local laws governing non-discrimination in employment. Peter Millar was founded in 2001 with a single cashmere sweater. Through this initial garment, an ethos emerged to embody luxury, elegance and a dedication to superior craftsmanship.

Today the brand has grown to include luxury performance sportswear, seasonal resort apparel, refined tailored clothing, and sartorial accessories. Each offering features the finest raw materials and fabric innovations while utilizing the world’s best yarn spinners, artisanal workshops and highly specialized factories. Peter Millar clothes and accessories are available online and in specialty retail stores and the most prestigious resorts.

Our global distribution includes North America, Europe, Asia, Australia and the South Pacific. Peter Millar is headquartered in Raleigh, North Carolina with a distribution center in Durham, North Carolina. Interested in exploring a different side of the brand family?

G/FORE is where style meets personality -- take a look at current opportunities here