AI Engineer

Ford • Dearborn, MI

3d • $99,600 - $192,900 • Hybrid

About The Position

Ford is seeking an AI Engineer to own the Industrial Systems Data Platform (ISDP) knowledge graph and its agent-facing serving layer end to end. ISDP unifies data from Product Development, Manufacturing, Quality, and Supply Chain applications. The role will build an AI-queryable knowledge graph—a BigQuery property graph derived from a canonical domain event store—and an MCP (Model Context Protocol) server that enables agents to reason over that data. The system will be developed, tested, and deployed to production using a Google Cloud Platform–native stack.

The engineer will model and evolve graph entities and relationships as new sources are onboarded, and build and operate MCP tools for graph queries, event-store queries, and schema/DDL discovery. They will establish tool contracts, context, and guardrails to support grounded, accurate agent responses, while ensuring secure, low-latency, cost-efficient service for interactive and batch workloads.

The role also owns monitoring and observability for the graph and MCP server, including data freshness, pipeline health, query latency and cost, tool-call success rates, and answer quality. The engineer will instrument SLOs, dashboards, alerting, and tracing, and drive incident response and reliability improvements. In collaboration with data engineers and application data source owners, they will onboard and validate data, establish contracts and quality checks, assist with mapping and troubleshooting, and contribute to governance, cataloging, and lineage.

The engineer will develop expertise in Ford's Industrial Systems and ISDP logical data model, including how programs, parts, ECUs, sites/plants, suppliers/organizations, requirements, verifications, quality problems, and warranty/returns are represented and interconnected across source applications. This is a hybrid position requiring onsite work four or more days per week. The salary grade is 7–8, with a stated range of $99,600–$192,900; the final grade and salary depend on candidate skills, experience, role scope, responsibility, and market value. Visa sponsorship is not available, and candidates must be legally authorized to work in the United States.

Requirements

• At least 5 years of experience with strong software engineering in Java and Python, production-grade testing, CI/CD, and code quality practices.
• At least 3 years of experience deploying data/AI systems to production on a GCP-native stack, including Vertex AI, BigQuery, Dataflow/Apache Beam, Pub/Sub, Cloud Run/GKE, Cloud Storage, and Cloud Build/Artifact Registry.
• At least 3 years of experience with graph data modeling and querying, including property graphs and GQL/graph query patterns; BigQuery property graphs or equivalent such as Neo4j/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/agent systems involving tool use, RAG/grounding, and integrating models via APIs such as Vertex AI or enterprise LLM gateways.
• Familiarity with MCP or comparable agent tool protocols.
• Observability expertise with 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.

Nice To Haves

• Familiarity with Dataplex/Data Catalog for governance, lineage, and business glossaries.
• Experience with streaming/CDC and event-driven architectures, including append-only/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/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 an 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 support grounded, accurate agent responses over the graph.
• Ensure low-latency, secure, and cost-efficient serving for interactive and batch agent workloads.
• Monitor and observe 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 continuous 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, logical-model mapping, 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 back-up 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.
• 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.

What This Job Offers

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