We're building an AI-enabled supply chain that senses, predicts, prescribes, and acts. As Principal AI Architect, you'll design and build enterprise-grade AI systems — from data pipelines and models to agents and applications — that run in production across our Supply Chain organization.
This is a hands-on technical role. You'll be in the architecture, in the code, and in the weeds of production systems. You'll design solutions, prototype approaches, write and review code, and unblock engineering teams building alongside you.
Responsibilities include but not limited to:
- Architect and help build AI, generative AI, and agentic AI solutions — from proof of concept through production — using Python, FastAPI, PyTorch, LangGraph, and AutoGen
- Design solution architecture across data pipelines (Snowflake, Databricks), models, agents, RAG pipelines, vector databases, APIs, and React-based applications on AWS and Azure
- Get hands-on with complex technical problems: debugging production issues, prototyping new approaches, and reviewing code and system design
- Lead architecture reviews and technical decision-making, weighing tradeoffs across performance, cost, scalability, and maintainability
- Use GitHub, GitHub Actions, and GitHub Copilot to build and ship faster — for your own work and across teams
- Partner directly with product, data engineering, AI engineering, and platform teams to solve real technical problems, not just review their plans
- Mentor engineers through pairing, code review, and hands-on problem-solving
- Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or related technical field
- 8+ years building production software, AI/ML systems, or data platforms
- 5+ years architecting and building production AI/ML solutions in Python, including LLMs, RAG architectures, and vector databases, on cloud-native infrastructure (AWS or Azure), with at least 1+ years of hands-on experience in agentic AI frameworks (e.g., LangGraph, AutoGen, or equivalent)
- Experience with modern MLOps practices and CI/CD (GitHub Actions or equivalent)
- Proven ability to take AI or software systems from concept through production, including debugging, performance tuning, and operational support
- Comfortable operating independently and making architecture calls with incomplete information
- Strong communication skills — able to explain technical tradeoffs to engineers, product partners, and senior leaders
- Experience with FastAPI or similar frameworks for building production AI/ML services
- Experience with PyTorch for model development, fine-tuning, or inference
- Experience with Snowflake and/or Databricks for data pipelines feeding AI/ML systems
Skills Required
- Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or related technical field
- 8+ years building production software, AI/ML systems, or data platforms
- 5+ years architecting and building production AI/ML solutions in Python, including LLMs, RAG architectures, and vector databases, on cloud-native infrastructure (AWS or Azure)
- 1+ years hands-on experience in agentic AI frameworks (e.g., LangGraph, AutoGen)
- Experience with modern MLOps practices and CI/CD (GitHub Actions or equivalent)
- Proven ability to take AI or software systems from concept through production, including debugging, performance tuning, and operational support
- Strong communication skills (explain technical tradeoffs to engineers, product partners, and senior leaders)
- Comfortable operating independently and making architecture calls with incomplete information
- Experience with FastAPI or similar frameworks for building production AI/ML services
- Experience with PyTorch for model development, fine-tuning, or inference
- Experience with Snowflake and/or Databricks for data pipelines feeding AI/ML systems
Stellantis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stellantis and has not been reviewed or approved by Stellantis.
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Pay Growth & Progression — Contract-driven increases lifted hourly wages roughly 25% over 4.5 years and restored cost-of-living adjustments, pushing top rates near $42 per hour by the end of the agreement. Union hourly positions appear to have benefited most since the 2023 deal.
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Affordable Benefits — UAW-represented hourly workers pay no premiums and about 3% of total healthcare costs while receiving comprehensive medical, dental, vision, and wellness coverage. This creates materially lower out-of-pocket costs for represented hourly roles.
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Retirement Support — Post-2007 hourly hires receive a 10% employer 401(k) contribution and legacy workers saw defined-benefit improvements with retiree bonuses. Salaried roles also cite a 401(k) with employer match and contribution up to a maximum of 8%.
Stellantis Insights
What We Do
Our storied and iconic brands embody the passion of their visionary founders and today’s customers in their innovative products and services: they include Abarth, Alfa Romeo, Chrysler, Citroën, Dodge, DS Automobiles, Fiat, Jeep®, Lancia, Maserati, Opel, Peugeot, Ram, Vauxhall and mobility brands Free2move and Leasys. Powered by our diversity, we lead the way the world moves – aspiring to become the greatest sustainable mobility tech company, not the biggest, while creating added value for all stakeholders as well as the communities in which we operate.
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