Director, AI/ML Engineering

Stellantis•Auburn Hills, MI

About The Position

The Director of AI/ML Engineering — North America builds and leads the North American AI/ML engineering organization, a team of 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 role requires current software-development experience and a record of shipping and operating end-to-end solutions, not only models, to complement a team with roots in data science and machine learning. The Director will build a North America team of 6–8 engineers, including hiring through an active recruiting pipeline, and own delivery and production health of the products the teams build. The AI & ML Engineering organization is global, so the role involves significant cross-region coordination and collaboration with globally dispersed project teams. Engineering leaders own products end-to-end, from design through production and into maintenance and optimization. Direction, requirements, and priorities are set in partnership with program and product-management teams. Success involves shaping requirements, using evidence to push back where needed, and building trust with those partners. The leader remains close to the work and is expected to contribute technically, including reading and reviewing code. The role delivers both agentic AI systems and generative AI workloads. Agentic systems are the primary growth area: the Director will lead development of tool-using, multi-step agents that orchestrate data, models, and services to automate engineering and quality workflows. Generative AI features—including summarization, retrieval-augmented generation, content generation, and conversational interfaces—are an established and continuing part of the portfolio. Solutions span data pipelines, model services, agents and generative components, APIs, and user-facing applications and dashboards. The Director sets engineering standards for architecture, code review, testing, and CI/CD; works with the dedicated MLOps team and prepares solutions to meet its production-release and operational readiness gates; and routes production-driven code changes back through the engineering teams. The role also champions AI-native engineering practices, including agentic development tooling and disciplined AI-assisted development. As a member of the global AI/ML Engineering leadership team, the Director contributes to organizational design, capacity planning, and balancing 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 across services, APIs, and user-facing touchpoints or applications.
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; the role expects depth in agentic systems.
Strong Python skills.
Experience with cloud platforms; AWS is preferred.
Experience with modern data/ML platforms such as Databricks or Spark.
Demonstrated success delivering in a matrixed model through program and product-management partnerships.

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.
Experience in automotive, industrial, IoT, or another regulated or embedded-adjacent domain; 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, including dashboards, internal tools, or product user interfaces.

Responsibilities

Build and lead the North America AI/ML engineering team of 6–8 engineers, including recruiting, coaching, performance management, and career development.
Maintain an active recruiting pipeline with external search partners and internal talent acquisition, and strengthen engineering craft through hiring.
Develop engineers toward full-stack AI/ML capabilities across data, modeling, services, and application layers.
Lead development of agentic AI capabilities, including agent architectures, orchestration frameworks, tool/API design for agent consumption, evaluation, and guardrails for autonomous behavior.
Deliver and evolve LLM-powered generative AI product features, including summarization, retrieval-augmented generation, content generation, and conversational interfaces.
Own end-to-end delivery of production AI/ML solutions spanning data pipelines, model services, agents, APIs, applications, and dashboards.
Set and enforce engineering standards for architecture, code review, testing, and CI/CD, while remaining hands-on and reading and reviewing code.
Work with the dedicated MLOps team to meet production-release and operational-readiness standards and gates, and route production-driven code changes back through the 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, delivery commitments, and evidence-based progress communication.
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 work, including organizational design, capacity planning, and balancing maintenance and optimization with new development.