AI Engineer, Industrial Systems Data Platform

Ford Motor Company

. Design, develop, test, and deploy the ISDP knowledge graph from the domain event store to Production using cloud-native data pipelines .

Posted 9/17/2026full-timeDearborn • Michigan • United StatesMid-LevelSenior💰 $99,600 - $192,900 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying cloud-native data pipelines and graph data modeling, with a strong focus on observability and data quality. Proficient in utilizing GCP-native tools and frameworks to ensure efficient and reliable data processing and querying.

Highest-signal resume keywords

Java Software EngineeringPython Software EngineeringGCP-Native Stack DeploymentGraph Data ModelingObservability Expertise

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Hard Skills

Graph Query Language (GQL)Dataflow / Apache BeamVertex AITerraformCI/CD PracticesData Quality FrameworksSchema ValidationEvent-Driven ArchitecturesCloud Monitoring/LoggingInfrastructure as Code

Soft Skills

Collaboration with Data EngineersTroubleshootingCommunication with Data Producers

Tools & Technologies

BigQueryPub/SubCloud RunGKECloud StorageCloud BuildOpenTelemetryDashboardsAlertingData Catalog

Industry Keywords

Data GovernanceData LineageManufacturing SystemsSupply Chain SystemsQuality SystemsStreaming/CDCAppend-Only Data ModelingUser-Facing ApplicationsZero-Downtime Data DeploymentsGrounding and Tool-Use

Tech Stack

Tools & technologies

ApacheBigQueryCloudGoogle Cloud PlatformJavaPythonTerraform

About the role

Key responsibilities & impact

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 as tools to consumers
Provide GQL graph query, event-store query, and schema/DDL discovery capabilities
Define tool contracts, context, and guardrails so agents produce grounded, accurate, non-hallucinated responses
Ensure low-latency, secure, and cost-efficient serving for interactive and batch agent workloads
Own monitoring and observability for the graph layer and MCP server, including 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
Partner with Data Engineers and Application Data Source Owners across Product Development, Manufacturing, Quality, and Supply Chain
Ingest and validate source 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

Requirements

What you’ll need

Bachelor's Degree in Computer Science, Information Technology, or Engineering or equivalent combination of education & experience
5+ years of experience with strong software engineering in Java and Python, with production-grade testing, CI/CD, and code quality practices
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
3+ years of experience with graph data modeling and querying, including property graphs and GQL / graph query patterns
3+ years of hands-on experience with Vertex AI, including agents, model serving, embeddings, and evaluation of agent answer quality
2+ years of experience building LLM/agent systems, including tool-use, RAG/grounding, and integrating models via APIs
Familiarity with MCP or comparable agent tool protocols
Expertise in observability, including Cloud Monitoring/Logging, OpenTelemetry, SLOs, dashboards, and alerting
3+ years of experience with Infrastructure as Code using 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/enterprise data
Candidates must be legally authorized to work in the United States
Preferred: Dataplex / Data Catalog, streaming/CDC, event-driven architectures, append-only/event-sourced data modeling, user-facing applications and dashboards, PLM/manufacturing/quality/supply-chain systems, data quality frameworks, schema evolution, and blue-green/zero-downtime data deployments

Benefits

Comp & perks

Immediate medical, dental, vision and prescription drug coverage
Flexible family care days
Paid parental leave
New parent ramp-up programs
Subsidized back-up childcare
Adoption and surrogacy expense reimbursement
Fertility treatments
Vehicle discount program for employees and family members
Management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
Generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off
Option to purchase additional vacation time
Visa sponsorship available