Director, AI/ML Engineering
CarMax View all jobs
- Richmond, BC
- Permanent
- Full-time
- Establish a technology vision and strategy for AI engineering ā 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 ā autonomous, multi-step AI agents that take action on behalf of customers and associates ā 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 ā 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
- Proven technology leader with experience building and managing highly engaged teams
- Passionate about AI engineering ā including agentic AI, generative AI, and AI automation ā as well as Data Science and Machine Learning engineering
- Persuasive communicator ā able to explain complex or intangible concepts to stakeholders at all levels
- Good listener ā 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
- 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