AI Engineer, Industrial Systems Data Platform (ISDP)

Ford; Dearborn, Northern (MI, KY); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Ford is hiring an AI Engineer for Enterprise Technology to own the ISDP knowledge graph end-to-end on a Google Cloud Platform stack. You will design, develop, test, and deploy the graph layer and MCP serving layer, turning industrial event data into a governed, queryable knowledge graph that powers engineering, manufacturing, quality, and supply-chain agents.

You will work with Data Engineers and application data owners to onboard data, define contracts, ensure data quality, and monitor system

Qualifications

• BS in CS/IT/Engineering or equivalent combination of education & experience.
• 5+ years of software engineering with Java and Python.
• 3+ years deploying data/AI systems to production on a GCP-native stack.

Responsibilities

• Design, develop, test, and deploy the ISDP knowledge graph from domain event store to Production.
• Build and operate the MCP server exposing the graph layer and event store.
• Ensure reliability, monitoring, and cost-efficient serving for interactive workloads.
• Collaborate with Data Engineers and Data Source Owners to onboard and validate data into ISDP.

Skills

Java

Python

CI/CD

Testing

Code quality

Education

Bachelor's degree in CS/IT/Engineering

Tools

Vertex AI

BigQuery

Dataflow / Apache Beam

Pub/Sub

Cloud Run / GKE

Cloud Storage

Artifact Registry

Job description

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.

Ford's Industrial Systems Data Platform (ISDP) unifies data fromProduct Development, Manufacturing, Quality, and Supply Chain applications into a single logical data model. We are building anAI-queryable knowledge graph over that data - a BigQuery property graph derived from a canonical domain event store - and anMCP (Model Context Protocol) server that lets agents reason over it.

We're looking for anAI Engineerto own this system end to end: design, develop, test, anddeploy the graph layer to Production on a Google Cloud Platform-native stack, and build the agent-facing serving layer on top of it. You will turn raw industrial event data into a governed, traversable graph that powers Ford's next generation of engineering, manufacturing, quality, and supply-chain agents.

Domain you'll master

Ford's Industrial Systems and the ISDP logical data model - how Product Development, Manufacturing, Quality, and Supply Chain applications describe programs, parts, ECUs, sites/plants, suppliers/organizations, requirements, verifications, quality problems, and warranty/returns - and how those entities interconnect in the knowledge graph.

Graph Layer

• Design, develop, test, and deploy the ISDP knowledge graph from the domain event store to Production using cloud-native data pipelines.
• Model and evolve the graph's entities and relationships as new data sources are onboarded.

MCP serving layer

• Design, build, and operate theMCP server that exposes the ISDP graph layer and event store as tools toconsumers- including GQL graph query, event-store query, and schema/DDL discovery.
• Define tool contracts, context, and guardrails so agents produce grounded, accurate, non-hallucinated responses over the graph.
• Ensure low-latency, secure, and cost-efficient serving for interactive and batch agent workloads.

Reliability, monitoring & observability

• Ownmonitoring and observabilityof the graph layer and the MCP server - data freshness, pipeline health, query latency/cost, tool-call success rates, and answer quality.
• Instrument SLOs, dashboards, alerting, and tracing; drive incident response and continuous reliability improvements.

Collaboration & data onboarding

1. Partner withData EngineersandApplication Data Source Ownersacross Product Development, Manufacturing, Quality, and Supply Chain toingest and validate their data into ISDP.
2. Establish data contracts, schema validation, and quality checks; support source owners through onboarding, mapping to the ISDP logical model, and troubleshooting.
3. Contribute to data governance, cataloging, and lineage for the graph and its sources.

Minimum Qualifications:

1. Bachelor's Degree in Computer Science, Information Technology, or Engineering or equivalent combination of education & experience
2. 5+ years of experience with Strong software engineering inJava, Python, with production-grade testing, CI/CD, and code quality practices.
3. 3+ years of experience with Hands-on experience deploying data/AI systems to Production on aGCP-native stack:Vertex AI, BigQuery,Dataflow / Apache Beam,Pub/Sub,Cloud Run / GKE,Cloud Storage, andCloud Build / Artifact Registry.