AI/ML Engineer - Supply Chain

Responsibilities As an AI/ML software engineer in the Supply Chain IT space, you will be the driving force for delivering Ford’s "AI-First" supply chain transformation. This role is focused on the applied implementation of AI. You will develop and deliver the integration of high-performance models to solve complex supply chain problems. Central to this role is the adoption of an AI-Driven Software Development Life Cycle (SDLC) leveraging agentic workflows, AI-assisted coding, and automated testing to deliver robust solutions at industrial speed. You will bridge the gap between abstract business problems and scalable technical execution. This role demands a blend of technical expertise in AI/ML, advanced analytics and data platform engineering, functional expertise in supply chain, and strong technical leadership to influence stakeholders and deliver transformative results. You will focus on establishing and standardizing the AI-based SDLC. You aren’t just building chatbots. You are building intelligent global supply chain solutions, helping the business manage risk, build resilience, and keep our factories running. Requirements Bachelor's degree in computer science, Information technology, Data Science, or related technical field. A Master’s degree is good to have 5+ years of software engineering experience. 3+ years of progressive experience in AI/ML, data science, or advanced analytics, with a proven track record of delivering production-grade solutions in large enterprise environments. Strong proficiency in Python and SQL. Familiarity with Graph Query Languages (e.g., Cypher) is good to have. Demonstrated experience with MLOps principles and tools (e.g., GCP AI Platform, Kubeflow, MLflow) and designing / implementing AI-specific SDLCs. Demonstrated experience in Infrastructure as Code (IaC) & CI/CD. Proficiencywith Terraform for managing cloud infrastructure, alongside modern CI/CD tools such asTekton, Jenkins, or GitHub Actions. Experience in LLMOps capability: Experience designing, deploying, and maintaining LLM-powered applications in production, with focus on prompt engineering, RAG pipelines, safety controls, hallucination mitigation, observability, cost optimization, and continuous testing and evaluation using metrics like accuracy,F1,BLEU, ROUGE etc and frameworks like RAGAS , DeepEval etc Strong technical expertise in cloud services (GCP/Vertex AI) and data integration patterns Strong analytical, problem-solving, and critical thinking skills. Exceptional communication & interpersonal skills, to translate complex AI logic into strategic recommendations for supply chain business leaders. Must have 3+ years of experience in Python, FastAPI/ Flask, REST APIs, SQL / NoSQL database, API authentication and authorization, Agent development andorchestration,Google ADK, Model Context Protocol, Prompt engineering and context management Must have 1-2 years of experience in CI/CD pipelines,Tekton, Git / GitHub Knowledge of RAG pipelines, Embeddings and vector search, LangChain/LangGraph, Kubernetes, Docker, Grafana or Dynatrace is desired by not a must have Proven track record of using AI tools to enhance personal or team productivity (e.g., Agentic workflows, RAG-based requirement synthesis). Experience in a product engineering role with a proven track record of translating business needs into technical specifications for applied AI implementation. Understanding semantic ontologies and how they enable advanced analytics. Functional understanding of supply chain operations, including demand & capacity planning, logistics, sustainability & risk management, resilience, etc. Ability to research and rapidly apply & build a functional prototype that meets Ford’s standards for security and scalability. #J-18808-Ljbffr Jobtailor