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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** Ford Motor Company - **Location:** Dearborn, MI, United States (Remote available) - **Salary:** $68,300.0 - $114,800.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Automated Storage and Retrieval Systems, BigQuery, Customer Information Control System (CICS), COBOL (Programming Language), Information Systems, Continuous Integration, IBM DB2, Relational Databases, Software Debugging, Graph Database, Python (Programming Language), PostgreSQL, Neo4j, Search Technologies, Systems Integration, TypeScript, Z/OS, Openapi, Google Cloud, Large Language Models, Multi-Agent Systems, Spring-boot, Backend, Kotlin, Event Driven Architecture, Containerization, Kubernetes, Information Technology, Apache Kafka, Splunk, Docker, Microservices - **Published:** August 29, 2026 - **Apply:** https://jobs.mitalent.org/job-seeker/job-details/JobCode/404844197 ## About the Role * 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+ years?in Python and Java (Kotlin, TypeScript 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, LangGraph, LangChain, or comparable. * Practical experience implementing?MCP (Model Context Protocol)?tool integrations, agent communication patterns, and AI observability. * Working experience with?vector search and hybrid retrieval, and with knowledge graphs or GraphRAG. * Strong backend fundamentals: Spring Boot, relational databases (PostgreSQL, DB2, or similar) including query and schema design, REST/OpenAPI, TDD, modern CI/CD. * Production experience on?Google Cloud Platform?(Vertex AI, Cloud Run, BigQuery) or an equivalent cloud. * Comfort operating in complex, multi-tier, legacy-integrated environments where change control and auditability matter. Even Better you'll have... * Semantic technologies, ontology engineering, or graph databases (Neo4j, Neptune, or similar). * Experience integrating with mainframe systems (COBOL, DB2 for z/OS, CICS) or comparable long-lived transactional cores. * Splunk SPL proficiency, including saved-search and dashboard authoring on large indexes. * Event-driven architectures (Pub/Sub, Kafka); containerization (Docker, Kubernetes). ## Description * 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-path?and?the 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?- SequentialAgent and LoopAgent 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. ## Related Videos - [Building a Multi-Agent Orchestration Engine That Actually Follows the Rules](https://www.wearedevelopers.com/videos/100159-building-a-multi-agent-orchestration-engine-that-actually-follows-the-rules) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [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) - [Can This Elephant Dance? IBM Bob and the Future of AI-First Software Development](https://www.wearedevelopers.com/videos/100256-can-this-elephant-dance-ibm-bob-and-the-future-of-ai-first-software-development) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Cyber Sleuth: Finding Hidden Connections in Cyber Data](https://www.wearedevelopers.com/videos/893-cyber-sleuth-finding-hidden-connections-in-cyber-data) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)