F

Ford Motor Company

Builds vehicles for drivers and commercial fleets

AI Engineer

AI Application Engineering +1Updated on Nov 11
Full-timeDearborn, MI, USA$99.6k - $192.9k

About the Job

Requirements

  • At least five years of experience in software engineering using Java and Python, including production-grade testing, continuous integration and continuous delivery, and code quality practices.
  • At least three years of hands-on experience deploying data or AI systems to production on a Google Cloud Platform-native stack, including Vertex AI, BigQuery, Dataflow or Apache Beam, Pub/Sub, Cloud Run or Google Kubernetes Engine, Cloud Storage, and Cloud Build or Artifact Registry.
  • At least three years of graph data modeling and querying experience, including property graphs and GQL or graph query patterns, using BigQuery property graphs or an equivalent such as Neo4j or Spanner Graph.
  • At least three years of hands-on experience with Vertex AI, including agents, model serving, embeddings, and evaluation of agent answer quality.
  • At least two years of experience building large language model or agent systems, including tool use, retrieval-augmented generation or grounding, and integrating models through APIs such as Vertex AI or enterprise LLM gateways; familiarity with Model Context Protocol or comparable agent tool protocols.
  • Expertise in observability, including Cloud Monitoring and Logging, OpenTelemetry, service-level objectives, dashboards, and alerting for data pipelines and services.
  • At least three years of experience with infrastructure as code using Terraform and secure-by-default engineering, including identity and access management, least privilege, and secrets management.
  • Ability to work directly with data producers to model and validate real-world industrial or enterprise data.

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 the graph's entities and relationships as new data sources are onboarded.
  • Design, build, and operate the Model Context Protocol server that exposes the ISDP graph layer and event store as tools to consumers, including GQL graph query, event-store query, and schema or data definition language discovery.
  • Define tool contracts, context, and guardrails so agents produce grounded, accurate responses over the graph without hallucinations.
  • 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, covering data freshness, pipeline health, query latency and cost, tool-call success rates, and answer quality.
  • Instrument service-level objectives, 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 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.

Desired Qualifications

  • Familiarity with Dataplex or Data Catalog for governance, lineage, and business glossaries.
  • Experience with streaming or change data capture 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 product lifecycle management or 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.

About the Company

Ford Motor Company

Builds vehicles for drivers and commercial fleets

Ford Motor Company designs and builds vehicles for individual drivers and commercial fleets worldwide, spanning Ford trucks and SUVs and Lincoln luxury models. Its Mustang sports car and Bronco off-road vehicles sit alongside gasoline, hybrid and electric products. The company sells vehicles, parts and accessories through dealers, while Ford Pro combines commercial vehicles with fleet software, charging and maintenance services; Ford Credit earns money from customer and dealer financing and leases. Connected services add subscriptions for vehicle features and business operations. Founded by Henry Ford in 1903, the company is headquartered in Dearborn, Michigan.

Company size
10,001+
Company stage
IPO
Headquarters
Dearborn, MI
Founded
1903

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