Director, AI/ML Engineering

Stellantis•Auburn Hills, MI

About The Position

The Director of AI/ML Engineering — North America builds and leads a North American organization of 6–8 full-stack AI/ML engineers delivering production AI products for engineering, quality, and vehicle-data use cases. This is a hands-on engineering leadership role focused on developing complete production solutions, including user-facing applications and touchpoints. The leader is expected to bring current software-development experience and a record of shipping and operating end-to-end solutions, strengthening a team whose roots are in data science and machine learning. The Director owns delivery and production health for the team’s AI/ML products, builds the team through recruiting and development, and coordinates significantly with a global organization. Product direction, requirements, and priorities are set in partnership with program and product-management teams. The role is responsible for shaping requirements, making evidence-based recommendations, and delivering within that partnership. Engineering leaders own products from design through production and into maintenance and optimization, and remain close to the work. The portfolio includes agentic systems as a primary growth area and generative AI workloads as an established, continuing area. The Director will lead development of tool-using, multi-step agents that orchestrate data, models, and services to automate engineering and quality workflows, including agent architectures, orchestration frameworks, APIs and tools, evaluation, and guardrails. The role also delivers LLM-powered features such as summarization, retrieval-augmented generation, content generation, and conversational interfaces. The Director leads end-to-end delivery across data pipelines, model services, AI components, APIs, and user-facing applications and dashboards. They set engineering standards for architecture, code review, testing, and CI/CD, and stay hands-on by reading and reviewing code. The team works closely with a dedicated MLOps team, building to its production-readiness standards and gates and routing production-driven code changes back through the engineering teams. The position also champions AI-native engineering practices, partners with program and product-management teams on scope, priorities, and delivery commitments, and coordinates across global data science, MLOps, and data engineering teams. As a member of the AI/ML Engineering leadership team, the Director contributes to organizational design, capacity planning, and balancing product maintenance and optimization with new development.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience.
At least 12 years of software engineering experience, including substantial hands-on solution development involving services, APIs, and user-facing applications or touchpoints.
Several years of experience leading engineering teams and managers.
Track record of shipping and operating production software and owning systems in production.
Practical experience delivering ML/AI-powered products.
Hands-on familiarity with LLM-based development across generative features and agentic systems, including tool use, orchestration, and multi-step autonomous workflows.
Strong Python skills.
Cloud experience; AWS is preferred.
Experience with modern data/ML platforms, such as Databricks or Spark.
Demonstrated success delivering in a matrixed model through partnerships with program and product-management teams.

Nice To Haves

Production experience with agent frameworks, agent evaluation, and guardrails for autonomous systems.
Experience adopting AI-assisted development tooling across an engineering team.
Automotive, industrial, IoT, or other regulated or embedded-adjacent domain experience; time-series or vehicle-data experience is a plus.
Experience growing a site or regional engineering hub, including hiring at pace through external partners.
Front-end or full-stack delivery experience with dashboards, internal tools, or product user interfaces.

Responsibilities

Build and lead the North American AI/ML engineering team of 6–8 engineers, including recruiting, coaching, performance management, and career development.
Maintain an active recruiting pipeline through external search partners and internal talent acquisition, raising engineering standards with each hire.
Develop engineers toward full-stack AI/ML capability across data, modeling, services, and application layers.
Lead the growth of agentic AI capability, including agent architectures, orchestration frameworks, tool and API design, evaluation, and guardrails for autonomous behavior.
Deliver and evolve generative AI product features, including summarization, retrieval-augmented generation, content generation, and conversational interfaces.
Own end-to-end delivery of production AI/ML solutions, including data pipelines, model services, APIs, agentic and generative components, applications, and dashboards.
Set and enforce engineering standards for architecture, code review, testing, and CI/CD; remain hands-on by reading and reviewing code.
Work with the dedicated MLOps team to meet production release and operation readiness standards and gates, and route production-driven code changes through the engineering teams.
Champion AI-native engineering practices, including agentic development tooling and disciplined, high-throughput AI-assisted development.
Partner with program and product-management teams on scope, priorities, and delivery commitments, communicating progress with evidence.
Coordinate with global teams and functional leads across data science, MLOps, and data engineering, aligning North American products with global platforms and standards.
Contribute to AI/ML Engineering leadership activities, including organizational design, capacity planning, and balancing maintenance and optimization with new development.