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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer, Industrial Systems Data Platform (ISDP) - **Company:** Ford Motor Company - **Location:** Dearborn, MI, United States - **Experience:** Expert - **Salary:** $99,600.0 - $192,900.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Google App Engines, BigQuery, Cloud Storage, Software Quality, Continuous Integration, Data Governance, Data Infrastructure, Data Flow Control, Graph Database, Monitoring of Systems, Identity and Access Management, Python (Programming Language), Key Management, Neo4j, Role-Based Access Control, Application Data, Software Engineering, Data Streaming, Enterprise Data Management, Data Logging, Cloud Monitoring, Large Language Models, Build Server, Event Driven Architecture, Build Management, Information Technology, Google Cloud Functions, Event Store, Machine Learning Operations, Terraform, Industrial Software, Data Pipelines, Apache Beam - **Published:** September 18, 2026 - **Apply:** https://www.careerjet.com/job/us34d3f8c60bc4219a9e15de321fcc1408/eaa ## About the Role * 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, 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., * 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. ## Description 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Making Data Warehouses fast. 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