AI Engineer

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

We're looking for an AI Engineer to own this system end to end: design, develop, test, and deploy 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.

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 the MCP server that exposes the ISDP graph layer and event store as tools to consumers — 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

• Own monitoring and observability of 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

• Partner with Data Engineers and Application Data Source Owners across Product Development, Manufacturing, Quality, and Supply Chain to ingest and validate their data into ISDP.
• Establish data contracts, schema validation, and quality checks; support source owners through onboarding, mapping to the ISDP logical model, and troubleshooting.
• Contribute to data governance, cataloging, and lineage for the graph and its sources.

Required

• 5+ years of experience with Strong software engineering in Java, Python, with production-grade testing, CI/CD, and code quality practices.
• 3+ years of experience with Hands-on experience deploying data/AI systems to Production on a GCP-native stack: Vertex AI, BigQuery, Dataflow / Apache Beam, Pub/Sub, Cloud Run / GKE, Cloud Storage, and Cloud Build / Artifact Registry.
• 3+ years of experience with graph data modeling and querying — property graphs and GQL / graph query patterns (BigQuery property graphs, or equivalent such as Neo4j/Spanner Graph).
• 3+ years of Hands-on experience with Vertex AI (Agents, model serving, embeddings) and evaluation of agent answer quality.
• 2+ years of Experience building LLM/agent systems: tool-use, RAG/grounding, and integrating models via APIs (e.g., Vertex AI or enterprise LLM gateways). Familiarity with MCP or comparable agent tool protocols.
• Observability expertise: Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting for data pipelines and services.
• 3+ years of experience with Infrastructure as Code (Terraform) and secure-by-default engineering (IAM, least privilege, secrets management).
• Ability to work directly with data producers to model and validate real-world industrial/enterprise data.

Preferred

• Familiarity with Dataplex / Data Catalog for governance, lineage, and business glossaries.
• Streaming/CDC and event-driven architectures; append-only/event-sourced data modeling.
• Design and build user-facing applications and dashboards that surface Knowledge Graph data to end users.
• Domain exposure to PLM / product development, manufacturing execution, quality, or supply-chain systems and their data.
• Data quality frameworks, schema evolution, and blue-green/zero-downtime data deployments.

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.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:
• Immediate medical, dental, vision, and prescription drug coverage
• Paid parental leave, new parent ramp-up programs, subsidized back-up child care 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
• Generous vacation time, sick/personal time, and paid holidays, including between Christmas Eve and New Year’s Day

This position is a salary grade 7-8 and ranges from $99,600-$192,900.

Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.

For more information on salary and benefits, click here:

Visa sponsorship is not available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

This position is hybrid with a requirement to be onsite four or more days per week.

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