Supply Chain Applied AI Engineer

Stellantis; Auburn Hills (MI); On-site; USD 120,000 - 160,000; Full time

Job summary

Stellantis is seeking an AI Engineer to join the Supply Chain AI Hub, translating business opportunities into deployable AI solutions across perimeters. You will frame viable use cases with regional stakeholders and external partners, moving from prototypes to reusable, deployment‑ready assets.

You will work with AI architecture, data engineers, and business teams to scale value while balancing speed, quality, and long‑term maintainability.

Qualifications

• Bachelor’s or Master’s degree in Engineering, AI, Computer Science or related field
• 8+ years of experience in Supply Chain with a focus on AI, ML, GenAI
• Hands‑on AI/ML/GenAI engineering background with strong technical curiosity and pragmatic build discipline
• Able to work closely with business stakeholders in iterative delivery, prototyping, and scaling contexts
• Demonstrated ability to operate independently and own production services end‑to‑end (design, build, deploy, monitoring, incident response) with minimal oversight
• Comfortable with Python, APIs, integrations and practical solution development in modern enterprise environments
• Interested in both innovation scouting and real delivery execution

Responsibilities

• Translate business problems into AI solution components, prototypes, experiments, and scalable approaches
• Work iteratively with business stakeholders to test ideas and validate value
• Distinguish exploratory work from reusable, industrialized deployment
• Contribute to solution logic, integrations, data connectivity and reusable components
• Align work with architecture standards and practical delivery constraints
• Maintain delivery momentum by surfacing blockers and risks to stakeholders
• Scout external innovations and partnerships for potential use
• Build assets with reuse in mind for regional deployment

Skills

AI/ML engineering

Python

APIs

Deployment readiness

Stakeholder communication

Education

Bachelor’s or Master’s degree in Engineering/AI/CS

Job description

About the Role: Join the Supply Chain AI Hub as an AI Engineer helping translate business opportunities into practical AI solutions across different Supply Chain perimeters. This role helps engage closely with business teams, regional stakeholders and external ecosystem players to frame the right use cases, scale value by moving from prototypes and experiments to reusable and deployment‑ready assets, and pioneer practical engineering approaches by testing innovations, scouting relevant solutions and contributing to real‑world AI delivery.

Key Interfaces

• Business stakeholders across supply, demand, operations and adjacent Supply Chain perimeters
• AI Architecture & Delivery Standards Lead
• Senior Data Engineers and data stakeholders
• Regional AI & Data Leads
• External ecosystem players, solution partners and relevant innovation providers when useful

Your Missions

Use‑Case Framing, Prototyping & Experimentation

• Translate business problems into practical AI solution components, prototypes, experiments and scalable technical approaches depending on the maturity of the use case
• Work iteratively with business stakeholders to test ideas early, challenge assumptions and keep technical ambition grounded in real operational value
• Help distinguish what should remain exploratory from what should move toward reuse, industrialization or broader deployment

Engineering, Integration & Delivery Support

• Contribute to solution logic, integrations, data connectivity and reusable technical components required by active AI use cases
• Align technical work with architecture standards, trusted‑deployment expectations and practical delivery constraints
• Help maintain delivery momentum while making early blockers, dependencies and risks visible to the right stakeholders

Innovation Scouting & External Ecosystem Engagement

• Maintain awareness of relevant external innovations, tools, partners and emerging AI approaches that could strengthen Supply Chain use cases
• Contribute informed recommendations on when external solutions, partnerships or rapid experimentation are worth exploring
• Help connect domain needs with relevant external capabilities without losing control of delivery practicality

Reuse, Scale & Regional Adaptation

• Build with reuse in mind so assets can evolve from early exploration to broader deployment across regions, use cases and business contexts
• Capture engineering learnings, patterns and playbooks that accelerate future delivery work
• Contribute to practical AI scale‑up by balancing speed, quality, experimentation and long‑term maintainability

Your Profile

• Hands‑on AI / ML / GenAI engineering background with strong technical curiosity and pragmatic build discipline
• Comfortable with Python, APIs, integrations and practical solution development in modern enterprise environments
• Able to work closely with business stakeholders in iterative delivery, prototyping and scaling contexts
• Interested in both innovation scouting and real delivery execution
• Structured, inventive and able to take ownership of a defined subset of a broader AI engineering scope

Skills You’ll Grow

• Exposure to a broad range of Supply Chain AI use cases and business contexts
• Experience balancing experimentation, engineering quality and deployment logic in real delivery settings
• Opportunity to deepen expertise in a specific domain while contributing to a wider AI engineering agenda

Why Join / Impact

• Work on AI engineering challenges directly tied to real Supply Chain business value
• Join a role broad enough to offer variety, while still allowing focused ownership on a defined perimeter
• Help shape practical AI solutions from early idea to credible deployment path

Basic Qualifications

• Bachelor’s or Master’s degree in Engineering, AI, Computer Science or related field
• 8 years of experience in Supply Chain with a focus on AI, ML, GenAI
• Hands‑on AI / ML / GenAI engineering background with strong technical curiosity and pragmatic build discipline
• Able to work closely with business stakeholders in iterative delivery, prototyping, and scaling contexts
• Demonstrated ability to operate independently and own production services end‑to‑end (design, build, deploy, monitoring, incident response) with minimal oversight
• Comfortable with Python, APIs, integrations and practical solution development in modern enterprise environments
• Interested in both innovation scouting and real delivery execution

At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future.