About the role

What will you do at Stellantis?

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

Qualifications

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

Which skills does this role require?

AI EngineeringMachine LearningGenerative AIPythonAPI IntegrationSupply Chain ManagementPrototypingSolution ArchitectureData ConnectivityInnovation ScoutingEnd-to-end Production ServicesTechnical DesignAIMLGenAIAPIsSupply ChainIndustrializationEnterprise EnvironmentsProduction ServicesMonitoringIncident ResponseData EngineeringScalabilityTechnical ArchitectureLLMsA/B Testing

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