Applied AI/ML Software Engineer-Supply Chain AI and Decision Intelligence

Ford • Dearborn, MI

2d • Hybrid

About The Position

We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

Enterprise Technology plays a critical part in shaping the future of mobility. If you’re looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people’s lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.
In this position...
As an Applied AI/ML Engineer in the Supply Chain AI and Decision Intelligence 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 (internal or external, e.g., from COTS products) onto Enterprise Knowledge Graphs 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. You aren’t just building chatbots. You are building the intelligence behind a global supply chain, helping the business manage risk, build resilience, and keep factories running.
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. with a particular focus on establishing and standardizing the AI-based SDLC across cross-functional teams.

Requirements

• Bachelor of Computer Science, Information Systems, Systems Programming or equivalent combination of relevant education and experience
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
• 3+ years of professional Software Development experience with proven progressive experience in AI/ML, data science, or advanced analytics, with a proven track record of delivering production-grade solutions in large enterprise environments.
• 2+ years in Python and SQL. Familiarity with Graph Query Languages (e.g., Cypher).
• 2+ years of demonstrated experience with MLOps principles and tools (e.g., Azure ML, AWS SageMaker, GCP AI Platform, Kubeflow, MLflow) and designing / implementing AI-specific SDLCs.
• 2+ years of experience designing, deploying, and maintaining LLM-powered applications in production, with focus on prompt engineering, RAG pipelines, safety controls, hallucination mitigation, observability, cost optimization, etc.
• 2+ years of technical expertise in cloud services (GCP/Vertex AI) and data integration patterns

Nice To Haves

• Master’s degree in Computer Science, Engineering, Data Science or related technical field
• AI-SDLC Experience: Proven track record of using AI tools to enhance personal or team productivity (e.g., Agentic workflows, RAG-based requirement synthesis).
• Requirement Engineering: Experience in a product engineering role with proven track record of translating business needs into technical specifications for applied AI implementation.
• Knowledge Graph: Understanding semantic ontologies and how they enable advanced analytics.
• COTS Integration: Experience integrating COTS AI solutions into an enterprise tech stack.
• Supply Chain Domain Knowledge: Functional understanding of supply chain operations, including demand & capacity planning, logistics, sustainability & risk management, resilience, etc.
• Research to Production: Ability to research and rapidly apply & build a functional prototype that meets Ford’s standards for security and scalability.
• Strong analytical, problem-solving, and critical thinking skills.
• Exceptional communication, interpersonal skills, and stakeholder management skills.

Responsibilities

• Business Requirement Gathering: Partner with supply chain functional leads to elicit and document business requirements and translate them into technical specifications for AI-driven decision support tools, ensuring every solution delivers measurable business value.
• Model Integration & Deployment: Act as the primary technical lead for applied AI implementation. Take pre-developed models from internal partners or 3rd-party vendors (COTS) and successfully deploy them within the supply chain GCP space.
• Graph-Based AI Implementation: Work closely with Knowledge Graph engineering teams to execute model interface against enterprise ontologies, you will design decision-intelligence frameworks that proactively identify and mitigate risks across the global N-tier supplier network. Simulate "what-if" scenarios using Generative AI and Graph analytics, and enable the supply chain to remain resilient against geopolitical, environmental, and logistical shocks, providing automated prescriptive solutions for supply-chain, logistics and capacity re-allocation before disruptions impact production .
• AI-Driven SDLC Execution: Champion and implement AI-assisted development practices. Implement agentic workflows (e.g., AutoGen, CrewAI) and use LLM-based tools (e.g., GitHub Copilot, automated PR agents, and AI-generated documentation) to accelerate delivery with high code quality for the Decision Intelligence platform
• Pipeline & MLOps/LLMOps Engineering: Design the "connective tissue" between Knowledge Graph updates and model inference engines. Establish rigorous guardrail frameworks for toxicity, hallucination rates, and latency. Maintain automated pipelines that ensure decision-support tools are always powered by the most current data.
• Technical Standardization: Develop reusable integration patterns and data contracts to ensure that AI solutions can be scaled across multiple business units without redundant engineering effort.

Benefits

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up childcare and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees