Solution Architect

Stellantis • Auburn Hills, MI

2d

About The Position

The Solution Architect is part of the PDT AI Solutions Program Team, which coordinates and manages efforts to apply AI-based technologies across the Product Development and Technology (PDT) organization. The team aims to enable engineers, executives, and others across PDT to use relevant AI technology in their daily work, with solutions that are production-grade, scalable, trustworthy, and adapted to Stellantis people.

The role proposes technical, AI-based solutions for problems or opportunities identified across PDT. It analyzes existing descriptions of needs, such as Product Requirements Documents (PRDs), and, when needed, gathers additional context and works with the Product Manager to extend the PRD. It then develops a high-level technical architecture to address the defined problem, including appropriate AI components and any other required elements, such as front end, back end, infrastructure, data pipelines, models, or data. The architect collaborates with the Product Manager, Project Manager, and technical implementation teams.

The team’s mission is to improve PDT efficiency, speed, inventiveness, and quality, as well as Stellantis customer satisfaction. It does this by establishing and maintaining projects for shared tools and resources that help PDT teams build their own AI applications and processes, and by delivering turnkey AI applications and processes for teams without the resources to build them independently, using current AI technology adapted to its users.

Requirements

• Bachelor’s degree.
• At least 5 years designing and delivering production software systems.
• At least 2 years developing or using machine learning, AI, or data-driven solutions.
• Proven ability to define service boundaries, APIs, and scalable architectures.
• Working knowledge of AI/ML system design, including data pipelines, deployment patterns, and operational monitoring.
• Strong data architecture fundamentals, including batch and streaming, modeling, and governance, and the ability to derive data requirements from product needs.
• Experience with cloud infrastructure and deployment patterns, and the ability to design secure, observable systems.
• Excellent technical documentation skills, including architecture diagrams, tradeoff analysis, and decision records.

Nice To Haves

• Experience architecting and delivering production LLM applications, including RAG, vector search, tool calling or agents, evaluation, and guardrails.
• Hands-on MLOps or platform experience, including CI/CD for ML, model registries, feature stores, monitoring, and drift detection.
• Experience in enterprise-scale or regulated environments and/or implementing responsible AI controls and auditability.
• Strong AI workload cost-modeling skills, including GPU serving, token-cost optimization, and capacity planning.
• A degree in an engineering field, such as computer, software, machine learning, intelligent systems, control systems, mechatronics, systems, or mechanical engineering, or in a science field such as physics or mathematics.
• Ability to work across teams.
• Ability to build agreement.
• Experience working with global teams.

Responsibilities

• Analyze existing descriptions of problems or needs where AI-based development may help, including Product Requirements Documents.
• Gather additional understanding and, as needed, extend the PRD in collaboration with the Product Manager.
• Create proposals for high-level technical architectures to solve defined problems, including AI components and other necessary components such as front end, back end, infrastructure, data pipelines, models, and data.
• Work in collaboration with the Product Manager, Project Manager, and technical implementation teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior