AI Engineering Practice Manager

Live the experience. From professional empowerment to continual learning opportunities. From ongoing investment in new and emerging technologies to a career of self-determination. At Ulta Beauty, our tech team is critical to our scalability—and is recognized that way. We’ve been defined as a “mature start-up.” A place where interdepartmental exposure, open doors, and genuine collaboration is ubiquitous. Where challenges come fast and furious, requiring agility, mental dexterity, and creativity. Where our passion for better solutions drives us and is core to who we are.

We’re engineering for the future of retail, and it’s no-holds-barred. But for those motivated by continual change and ambiguity, by superior leadership, by whip smart colleagues who will press you daily for your very best, you’ll find that virtually nothing’s impossible at Ulta Beauty.

THE IMPACT YOU CAN HAVE: 

The Manager, AI Engineering Practice Lead is the enterprise discipline leader responsible for AI engineering rigor, frameworks, and governance across the AI portfolio. This role establishes and enforces the standards by which AI solutions are built, tested, and deployed, ensuring consistency, quality, and operational readiness across Guest, Associate, and Enterprise domains.

The Manager provides horizontal leadership to AI Engineers embedded within delivery pods, shaping engineering best practices, capability development, and quality assurance. This role partners closely with Enterprise Architecture and platform teams to ensure AI engineering standards align with broader technology guardrails.

Success is measured by engineering quality, consistency of deployment practices, practitioner maturity, and the organization’s ability to deliver production-grade AI solutions with confidence.

YOU'LL ACCOMPLISH THESE GOALS BY: 

• Define and govern AI engineering standards, including build patterns, testing frameworks, deployment protocols, and production-readiness criteria.
• Establish quality controls for AI systems, including integration validation, performance testing, monitoring coverage, and responsible AI compliance.
• Provide input into enterprise operational standards to ensure AI-specific considerations are incorporated appropriately.
• Conduct engineering design and readiness reviews for high-impact or complex AI initiatives prior to production deployment.
• Serve as the escalation authority for novel or high-complexity engineering challenges.
• Ensure consistency in engineering approaches across delivery pods to reduce technical debt and fragmentation.
• Contribute to workforce planning, role definition, and career path development for AI Engineering practitioners.
• Mentor senior engineers and promote continuous improvement in AI engineering practices.
• Identify skill gaps and partner with leadership to strengthen enterprise AI engineering capability.
• Contribute to solution design and engineering approaches for new, novel, or strategically significant AI initiatives.
• Advise senior leadership on emerging AI engineering practices and implications for delivery models.

ESSENTIALS FOR SUCCESS: 

• 8+ years of progressive experience in software engineering, AI engineering, or ML systems development, including leadership in enterprise-scale environments.
• Preferred: Advanced degree (Masters / PhD)  in Computer Science, Mathematics, Physics, Statistics or other quantitative field
• Demonstrated experience establishing engineering standards, governance frameworks, and quality controls across multiple concurrent initiatives.

• Hands-on experience delivering production-grade AI/ML systems from development through deployment and monitoring.
• Strong expertise in cloud-native environments (GCP, Azure, AWS) and modern AI system integration patterns.
• Experience working in cross-functional delivery models with embedded engineering teams.
• Proven ability to influence without direct authority across technical and domain teams.
• Exposure to responsible AI principles and tooling including fairness testing, explainability techniques, and model risk governance.
• Experience with LLM-based architectures, RAG systems, and generative AI evaluation frameworks.

• Retail industry experience preferred

#LI - HYBRID

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At Ulta Beauty (NASDAQ: ULTA), the possibilities are beautiful. Ulta Beauty is the largest North American beauty retailer and the premier beauty destination for cosmetics, fragrance, skin care products, hair care products and salon services. We bring possibilities to life through the power of beauty each and every day in our stores and online with more than 25,000 products from approximately 500 well-established and emerging beauty brands across all categories and price points, including Ulta Beauty’s own private label. Ulta Beauty also offers a full-service salon in every store featuring—hair, skin, brow, and make-up services.

We will consider for employment all qualified applicants, including those with arrest records, conviction records, or other criminal histories, in a manner consistent with the requirements of any applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, and the New York City Fair Chance Act.