AI Engineer

Ford Motor • Dearborn, MI

2d • Hybrid

About The Position

Ford is seeking an AI Engineer to own the Industrial Systems Data Platform (ISDP) knowledge graph and agent-facing serving layer end to end. ISDP unifies data from Product Development, Manufacturing, Quality, and Supply Chain applications in a single logical data model. The role will build a BigQuery property graph derived from a canonical domain event store and an MCP (Model Context Protocol) server that enables agents to reason over the data. The engineer will design, develop, test, and deploy the graph layer to production on a Google Cloud Platform-native stack and build the serving layer for Ford's engineering, manufacturing, quality, and supply-chain agents.

The position includes evolving graph entities and relationships as data sources are added; building and operating an MCP server with graph and event-store queries and schema discovery; defining tool contracts and guardrails for grounded agent responses; and ensuring secure, low-latency, cost-efficient service. The engineer will own monitoring and observability, including data freshness, pipeline health, query latency and cost, tool-call success, and answer quality. The role also partners with data engineers and source owners on onboarding, data contracts, schema validation, quality checks, governance, cataloging, and lineage.

The successful candidate will develop expertise in Ford's Industrial Systems and ISDP logical data model, covering data and relationships across programs, parts, ECUs, sites/plants, suppliers/organizations, requirements, verifications, quality problems, and warranty/returns. This is a hybrid position requiring onsite work four or more days per week.

Requirements

• At least 5 years of strong software engineering experience with Java and Python, including production-grade testing, CI/CD, and code quality practices.
• At least 3 years of hands-on experience deploying data or AI systems to production on a GCP-native stack, including Vertex AI, BigQuery, Dataflow or Apache Beam, Pub/Sub, Cloud Run or GKE, Cloud Storage, and Cloud Build or Artifact Registry.
• At least 3 years of graph data modeling and querying experience, including property graphs and GQL or graph query patterns (BigQuery property graphs or equivalents such as Neo4j or Spanner Graph).
• At least 3 years of hands-on experience with Vertex AI, including agents, model serving, embeddings, and evaluation of agent answer quality.
• At least 2 years of experience building LLM or agent systems involving tool use, RAG/grounding, and model integration via APIs such as Vertex AI or enterprise LLM gateways.
• Familiarity with MCP or comparable agent tool protocols.
• Observability expertise, including Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting for data pipelines and services.
• At least 3 years of experience with Terraform and secure-by-default engineering, including IAM, least privilege, and secrets management.
• Ability to work directly with data producers to model and validate real-world industrial or enterprise data.
• Must be legally authorized to work in the United States; visa sponsorship is not available.

Nice To Haves

• Familiarity with Dataplex or Data Catalog for governance, lineage, and business glossaries.
• Experience with streaming/CDC and event-driven architectures, including append-only or event-sourced data modeling.
• Experience designing and building 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.
• Experience with data quality frameworks, schema evolution, and blue-green or zero-downtime data deployments.

Responsibilities

• Design, develop, test, and deploy the ISDP knowledge graph from the domain event store to production using cloud-native data pipelines.
• Model and evolve graph entities and relationships as new data sources are onboarded.
• Design, build, and operate the MCP server, exposing the ISDP graph layer and event store through tools for GQL graph queries, event-store queries, and schema/DDL discovery.
• Define tool contracts, context, and guardrails to help agents produce grounded and accurate responses over the graph.
• Ensure low-latency, secure, and cost-efficient serving for interactive and batch agent workloads.
• Own monitoring and observability of the graph layer and MCP server, including data freshness, pipeline health, query latency and cost, tool-call success rates, and answer quality.
• Instrument SLOs, dashboards, alerting, and tracing; drive incident response and ongoing reliability improvements.
• Partner with Data Engineers and Application Data Source Owners across Product Development, Manufacturing, Quality, and Supply Chain to ingest and validate data into ISDP.
• Establish data contracts, schema validation, and quality checks; support source owners with onboarding, mapping to the ISDP logical model, and troubleshooting.
• Contribute to data governance, cataloging, and lineage for the graph and its sources.

Benefits

• Immediate medical, dental, vision, and prescription drug coverage.
• Paid parental leave, new parent ramp-up programs, and subsidized backup child care.
• Family-building benefits including adoption and surrogacy expense reimbursement and fertility treatments.
• Vehicle discount program for employees and family members, and management leases.
• Tuition assistance.
• Employee resource groups.
• Paid time off for individual and team community service.
• Vacation time, sick/personal time, and paid holidays, including between Christmas Eve and New Year’s Day.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed