AI Build Engineer Manager

Aptiv•Troy, MI

16d•Onsite

About The Position

AI BUILD ENGINEER MANAGER Important Company Update – Please Read Before Applying. On January 22, 2025, Aptiv announced its decision to separate its EDS division to form two separate independent companies: https://www.automotiveworld.com/news-releases/aptiv-announces-intention-to-separate-its-electrical-distribution-systems-business/Our solutions are central to enabling the next generation of electrified, automated, and connected vehicles, and we are committed to innovation, sustainability, and engineering excellence. We are looking for talented individuals who are excited by the opportunity to help shape the future of EDS and delivering industry-leading solutions to the world’s top automotive manufacturers. Why join Aptiv? You'll have the opportunity to work on cutting-edge applications, develop breakthrough technologies, and deliver innovative solutions to some of the world’s leading automotive brands. See your work come to life on the road—helping make mobility safer, greener, and more connected. Ready to shape the future of mobility with us? YOUR ROLE The AI Build Engineer is a high‑impact technical leader within the Enterprise Architecture (EA) team, operating at the intersection of strategic vision and hands‑on engineering. Serving as the execution layer of Enterprise Architecture’s AI strategy, this role transforms conceptual patterns into validated, repeatable implementation blueprints. You are a hybrid architect‑developer who excels at translating complex AI concepts—such as Agentic workflows, orchestration patterns, and RAG architectures—into “Golden Path” reference implementations that enable product teams to build with speed, security, and consistency. Your mission is to accelerate the organization’s AI capabilities by creating reusable codebases, containerized patterns, and enterprise-ready engineering standards that guide how AI solutions are designed and scaled.

Requirements

Programming: Mastery of Python (FastAPI, LangChain, LlamaIndex); ability to build lightweight UIs using Streamlit or React for demos
AI/ML: Strong hands-on experience integrating LLMs, building RAG pipelines, and working with vector indexing (e.g., Pinecone, Weaviate, Azure AI Search)
Cloud & Infrastructure: Deep proficiency in Azure and/or AWS AI services, serverless inference, and managed Kubernetes platforms
Containers: Expert-level skills in Docker, Helm, Kubernetes, and CI/CD pipelines (GitHub Actions, Azure DevOps) for AI workloads
Ability to work onsite in Troy, MI
Must be legally able to work in the United States without requirement of any type of visa sponsorship or transfer now, or at any time in the future

Nice To Haves

Experience with LLM Ops frameworks: model evaluation (Ragas, Arize Phoenix), monitoring, versioning, and drift analysis
Hands‑on exposure to model fine‑tuning techniques (LoRA / QLoRA) and domain specialization
Familiarity with Enterprise Architecture frameworks (TOGAF or similar)