Director, AI/ML Engineering

About the role

CarMax, the way your career should be!

Key Role Responsibilities

• Establish a technology vision and strategy for AI engineering — spanning agentic AI, generative AI, AI workflow automation, machine learning engineering, platform, and services, focusing on business outcomes tracked via key metrics, including overall financial management
• Define and execute a roadmap for Agentic AI systems — autonomous, multi-step AI agents that take action on behalf of customers and associates — integrating with existing ML and data science platforms
• Lead the adoption of generative AI technologies (including large language models and multimodal AI) to create differentiated customer experiences, associate tools, and internal productivity solutions
• Architect and govern AI workflow and automation pipelines that connect generative AI, agentic components, and traditional ML models into end-to-end intelligent business processes
• Lead and develop a 40+ member team (FTEs & contractors) responsible for feature engineering, agentic AI development, generative AI engineering, ML engineering, automation, and ML Ops for data science models
• Partner with Technology and Product leadership to define, drive, and deliver our AI/ML services to power the brand's omni-channel front-end experiences (website, mobile apps, in-store experience)
• Closely collaborate with data science and leadership to identify solutions, prioritize the roadmap and ensure delivery commitments
• Foster a product engineering culture within the team and establish best practices around discovery, prototyping, continuous and rapid testing, and learning, with a relentless focus on delivering customer value
• Establish responsible AI governance practices, including safety, bias mitigation, explainability, and compliance guardrails for generative and agentic AI systems
• Collaborate with other Product Managers and Architects on the design and integration with other products and/or technology platforms
• Collaborate with other key stakeholders (e.g., legal, security, etc.) to ensure product features meet all security and privacy requirements — with particular attention to data governance and safety requirements for generative AI and agentic systems
• Partner with Reliability Engineering team to ensure proper controls have been implemented for proactive monitoring of critical product features, availability, and stability

Qualifications and Requirements

• Proven technology leader with experience building and managing highly engaged teams
• Passionate about AI engineering — including agentic AI, generative AI, and AI automation — as well as Data Science and Machine Learning engineering
• Persuasive communicator – able to explain complex or intangible concepts to stakeholders at all levels
• Good listener – weighs input from multiple perspectives when forming opinions and recommendations
• Collaborative and team-oriented work approach
• Experience gaining consensus among a large, diverse group of stakeholders
• Experience managing, training and mentoring others in Engineering methodologies and best practices
• Able to easily motivate and inspire team members, peers, stakeholders and executives
• Innovative; thinks beyond boundaries
• Analytical; solves problems at root cause and prioritizes effectively
• Continuous improvement mentality; never satisfied
• Comfortable speaking to large audiences and executives
• Flexible and open-minded; proactively seeks input from others
• Entrepreneurial drive and spirit; enjoys working in a fast-paced environment
• Handles constructive criticism with ease; adapts easily and efficiently to change

Education and/or Experience

• BA/BS Degree required. Master's Degree a plus.
• 10+ years' experience in AI engineering, generative AI, or Data Science/Machine Learning or related engineering field. Experience with large language models (LLMs), agentic AI frameworks, and AI automation platforms is highly preferred. ML Ops experience is a plus.
• 5+ years' experience managing direct reports
• Experience with lean/agile development processes
• Hands-on familiarity with generative AI tools and platforms (e.g., OpenAI, Anthropic, AWS Bedrock, Azure OpenAI) and agentic frameworks (e.g., LangChain, AutoGen, or similar)
• Experience designing and deploying AI workflow automation solutions integrating LLMs, APIs, and traditional ML models into cohesive business processes