Principal AI Solution Architect

About Ulta Beauty, Inc.

We are Ulta Beauty, the largest North American beauty retailer and a leading destination for cosmetics, fragrance, skin care, hair care, and salon services. Our technology organization is central to our growth, known for collaboration, ongoing learning, and rapid innovation in a fast-moving, startup-like environment.

The Role

We are seeking a high-impact Principal AI Solution Architect to help shape the future of retail through advanced AI capabilities, technical leadership, and enterprise-scale delivery.

Responsibilities

• We oversee the architectural design and delivery of AI, ML, and agentic solutions across multiple delivery pods, ensuring consistency and business alignment.
• We participate in Architecture Review Board discussions and provide senior-level guidance on AI initiatives.
• We manage and coach a high-performing team of solution, platform, and MLOps architects, setting performance expectations and growth plans.
• We define and execute the architecture team blueprint, including technical SME coverage and resource planning.
• We work within the Enterprise Architecture organization to ensure AI initiatives meet infrastructure, security, and data governance standards while helping shape those standards.
• We collaborate with other enterprise architects to establish and scale AI principles, platform standards, and integration patterns.
• We lead the design and rollout of agentic workflows and autonomous systems, including multi-agent orchestration, tool integration, and feedback loops.
• We establish and enforce architecture standards for model selection, retrieval-augmented generation patterns, and agent reasoning paths to balance cost, speed, and accuracy.
• We define the 12–24 month AI roadmap and evaluate emerging technologies to determine whether to build, buy, or partner.
• We coordinate with product owners and pod leads to allocate architectural capacity across priorities while minimizing technical debt.
• We address AI-related risks such as ethics, bias, hallucinations, and data privacy across the portfolio.
• We communicate architectural trade-offs to executive leadership and translate technical progress into business value and return on investment.
• We mentor internal team members and cross-functional partners in AI, ML, and NLP methods and practices.

Requirements

• We require a masters degree in Computer Science, Data Science, AI/ML, or equivalent professional experience; a PhD is preferred.
• We look for 12+ years of experience in software engineering and systems architecture, including at least 5 years leading large-scale AI production environments.
• We need experience managing architects or technical leads and coordinating multiple concurrent workstreams or pods.
• We value deep expertise in the modern AI stack, including LLM orchestration tools such as LangChain and LlamaIndex, vector databases like Pinecone and Milvus, and traditional ML frameworks such as TensorFlow and Scikit-Learn.
• We require hands-on experience designing agentic systems, autonomous workflows, or cognitive architectures.
• We expect strong knowledge of platform architecture and MLOps, including Kubernetes, model serving technologies such as BentoML, TGI, and vLLM, and automated retraining pipelines.
• We need experience working within and influencing enterprise architecture frameworks and operating in complex governance, risk, and compliance environments.
• We require hands-on experience with one or more cloud platforms, such as Google Cloud, Azure, or AWS.
• Experience in retail or e-commerce is preferred.
• We expect the ability to stay current with emerging AI methods and technologies and assess their business potential.
• We require excellent verbal and written communication skills, including the ability to produce clear architectural diagrams and white papers for technical and non-technical audiences.
• We value experience presenting and preparing materials for executive-level stakeholders.

Tech Stack

• AI
• AWS
• Architect
• Azure
• Cloud
• Kubernetes
• LLM
• Machine Learning
• Security
• TensorFlow

Benefits & Perks

• Paid time off
• Health coverage
• Dental
• Vision
• Life insurance
• Disability benefits
• Potential bonus compensation for eligible associates