Software and AI Engineer

We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.

The Ford Motor Credit Company team helps put people behind the wheels of great Ford and Lincoln vehicles. By partnering with dealerships, we provide financing, personalized service and professional expertise to thousands of dealers and millions of customers in over one hundred countries around the world.

• Ford Motor Credit Company's Pinnacle Loan Originations platform underwrites and funds a significant share of the vehicles Ford sells worldwide. It is a mission-critical, multi-tier system: a mainframe core (COBOL, DB2, CICS) that executes the money-path decisioning, a Java/Spring services tier that orchestrates business workflows, GCP Cloud Run microservices at the digital edge, and Splunk-driven observability across the estate.
• We are building an AI enablement layer on top of this platform — a set of production capabilities that make Pinnacle faster to operate, easier to debug, and more discoverable to the engineers and analysts who depend on it.

• Read the whole stack, then change it.
  
  Diagnose production issues across the mainframe (COBOL, DB2, CICS), the Java/Spring services tier, and Cloud Run microservices. Ship the fix on the money-pathandthe corresponding improvement to agent tooling and knowledge substrate in the same change set.
• Design and operate the MCP tools layer.
  
  Build least-privilege, per-call-audited MCP servers over DB2, Splunk, and GCP. Provenance, PII handling.
• Build production multi-agent workflows on Google ADK— Sequential Agent and Loop Agent compositions, creating and managing Agent workflows, including escalation-containment patterns — for Splunk → DB2 → GCP error triage, ADR authoring, and originations debugging.
• Own the knowledge graph and retrieval work end-to-end.
  
  Model the loan originations ontology (VIN, dealer, offer, program eligibility, environment topology). Implement hybrid vector + graph retrieval. Every RAG-produced answer must be defensible under audit.
• Ship deterministic backend services in Java/Kotlin + Spring Boot on GCP— the audit envelope, provenance store, and human-in-the-loop review surfaces where non-determinism is unacceptable.
• Author ADRs in ADR-driven-development, OKF business-logic documents, skill files, and Splunk saved-search catalogs. Pair with teammates on the hard debugging sessions. The write-up is part of 'done.'
• Track mean time from 'agent cannot handle this' to 'agent handles this autonomously,' and publish the trend monthly.
• Create evaluations and an evaluation runner for all AI tools and agents built by you and the team.
• Publish, monthly, the change types you've made cheaper — mean time from 'agent doesn't know this' to 'agent handles it autonomously.'
• Automate test-case generation, evaluation, and grading for both brownfield and greenfield applications, ensuring coverage, repeatability, and measurable quality improvements.

• Bachelor's or Master’s degree in Computer Science, Information Systems, or a related field — or equivalent professional experience.
• 7+ years building and operating production-grade backend systems as a hands-on engineer.
• 5+ yearsin Python and Java (Kotlin, Type Script a plus).
• Atleast 1 year of experience in shipping AI-enabled applications in production — agent frameworks, retrieval systems, or LLM-backed services.
• Demonstrated experience with agent orchestration frameworks —Google ADK, Lang Graph, Lang Chain, or comparable.
• Practical experience implementingMCP (Model Context Protocol) tool integrations,…