Principal AI Architect - Supply Chain

About the role

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 where you'll be in the architecture, in the code, and in the weeds of production systems.

Responsibilities

• 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

Requirements

• 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

Preferred Qualifications

• 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

Benefits

• Comprehensive Health & Well-being Coverage: Medical, dental, vision, and prescription drug coverage from day one, plus an Employee Assistance Program (EAP) for confidential support
• Family Building Benefit: Support for fertility and infertility treatments, adoption services, and gestational surrogacy
• Generous Paid Time Off: 17+ paid holidays (including year-end shutdown from December 24th through New Year’s Day), vacation, float & wellbeing days, sick time, and fully paid parental leave
• Competitive Retirement Savings Plans: Employer match on 401k, Roth, and Catch-Up contributions, plus an employer contribution even if you don’t contribute
• Income Protection & Insurance Options: Employer-provided and voluntary life insurance, group accident, critical illness, and other coverage options
• Company Vehicle Lease Program: Eligible employees and their families can lease Stellantis vehicles with insurance, maintenance, and unlimited miles included, plus exclusive discounts on Stellantis products
• Support for Growth and Giving Back: Tuition reimbursement, student loan refinancing programs, and 18 paid volunteer hours annually