Full Stack Software Engineer, AI Integration

at Ford · Auto · Dearborn, MI +1 · Enterprise Technology

Full Stack Software Engineer focused on integrating AI, specifically LLMs, into applications. The role involves architecting systems with autonomous agents, utilizing a Model Context Protocol for live data interaction, and providing real-time streaming experiences. Key responsibilities include designing agentic loops, implementing tool-use capabilities, integrating with proprietary data silos, developing high-concurrency back-ends and streaming front-ends, optimizing RAG pipelines, and establishing AI evaluation and observability.

What you'd actually do

  1. Design Autonomous Loops: Transition from linear "chain" workflows to self-correcting agentic loops using frameworks like LangChain, LlamaIndex, or CrewAI.
  2. Tool-Use Architecture: Design and implement robust "tool-calling" capabilities, ensuring LLMs can reliably interact with external APIs and microservices.
  3. MCP Integration: Build and maintain Model Context Protocol (MCP) servers to bridge the gap between LLMs and our proprietary data silos securely and in real-time.
  4. High-Concurrency Back-end: Develop asynchronous Python (FastAPI) or Java services optimized for long-running AI tasks and token streaming.
  5. Streaming Front-end: Build responsive, stateful UIs in React or Angular that handle complex AI interactions (streaming text, generative UI components, and multi-modal feedback).

Skills

Required

  • BS in Computer Science or Engineering related field
  • 5+ years of total software engineering experience
  • 2+ years focused on AI integration
  • 2+ years of professional experience with LangChain, LlamaIndex, or Google ADK
  • GitHub Copilot (IDE & CLI), Claude Code, Cursor, or similar agentic coding assistants
  • Ability to architect end-to-end AI-native systems
  • 3+ years designing and building Python (FastAPI/Flask) or Java (Spring Boot) services
  • 2+ years designing real-time, streaming UI systems in React or Angular
  • Expert knowledge of SQL (PostgreSQL/pgvector) and Vector Databases (Chroma, Qdrant, or Pinecone)
  • Hands-on experience with GCP (Vertex AI) or AWS (Bedrock)
  • Experience with Git, Docker, Kubernetes,Terraform, and CI/CD (GitHub Actions/Jenkins)

Nice to have

  • The Agentic Mindset: You have a proven track record of moving models from "answering questions" to "completing multi-step tasks."
  • Prompt Engineering as Code: You treat prompts as production code—versioned, tested, and optimized for deterministic outcomes.
  • MCP Expertise: You understand the future of data grounding and have experimented with or implemented Model Context Protocol servers.
  • Growth Agility: You stay ahead of the curve, moving fluently from RAG-based architectures to Long-Context model strategies as the landscape shifts.

What the JD emphasized

  • AI-native applications
  • autonomous agents
  • agentic loops
  • tool-calling
  • streaming experiences
  • AI Evals
  • hallucination rates
  • latency
  • cost
  • automated AI benchmarking

Other signals

  • autonomous agents
  • LLMs as core engine
  • agentic loops
  • tool-use
  • streaming experiences
Read full job description

We are moving beyond "Chatbots." We are building AI-native applications where LLMs aren’t just features—they are the core engine. As a AI Full Stack Engineer, you will architect systems where autonomous agents navigate complex business logic, utilize the Model Context Protocol (MCP) to interact with live data, and provide users with seamless, real-time streaming experiences.

You aren't just a software engineer; you are an AI Orchestrator bridging the gap between non-deterministic model logic and high-performance software engineering.

1. Agentic Orchestration & Logic Design Autonomous Loops: Transition from linear "chain" workflows to self-correcting agentic loops using frameworks like LangChain, LlamaIndex, or CrewAI. Tool-Use Architecture: Design and implement robust "tool-calling" capabilities, ensuring LLMs can reliably interact with external APIs and microservices. MCP Integration: Build and maintain Model Context Protocol (MCP) servers to bridge the gap between LLMs and our proprietary data silos securely and in real-time.

2. Full Stack AI Delivery High-Concurrency Back-end: Develop asynchronous Python (FastAPI) or Java services optimized for long-running AI tasks and token streaming. Streaming Front-end: Build responsive, stateful UIs in React or Angular that handle complex AI interactions (streaming text, generative UI components, and multi-modal feedback). Advanced RAG Pipelines: Go beyond basic vector search. Implement re-ranking, query transformation, and embedding optimization to maximize retrieval precision.

3. AI Engineering Excellence Context Optimization: Master the "Context Window" by implementing prompt compression and "lost-in-the-middle" mitigation strategies. Evaluation & Observability: Establish AI Evals to quantify hallucination rates, latency, and cost. Lead the shift from "vibes-based" testing to rigorous, automated AI benchmarking. DevOps/MLOps: Manage CI/CD pipelines that include vector database migrations and automated prompt versioning.

  • BS in Computer Science or Engineering related field

  • 5+ years of total software engineering experience

  • 2+ years focused on AI integration

  • Technical Requirements:

    • AI Frameworks: 2+ years of professional experience with LangChain, LlamaIndex, or Google ADK.
    • AI Development Tools: GitHub Copilot (IDE & CLI), Claude Code, Cursor, or similar agentic coding assistants.
    • System Design: Ability to architect end-to-end AI-native systems—covering data flow, latency budgets, failure modes, scaling strategies, and LLM integration patterns.
    • Back-end Mastery: 3+ years designing and building Python (FastAPI/Flask) or Java (Spring Boot) services, with expertise in async patterns, distributed systems, and API design.
    • Front-end Precision: 2+ years designing real-time, streaming UI systems in React or Angular, with a focus on state management, WebSocket/SSE patterns, and component architecture.
    • Data Architecture: Expert knowledge of SQL (PostgreSQL/pgvector) and Vector Databases (Chroma, Qdrant, or Pinecone).
    • Cloud Infrastructure: Hands-on experience with GCP (Vertex AI) or AWS (Bedrock).
    • Modern DevOps: Experience with Git, Docker, Kubernetes,Terraform, and CI/CD (GitHub Actions/Jenkins).

  • What Sets You Apart:

    • The Agentic Mindset: You have a proven track record of moving models from "answering questions" to "completing multi-step tasks."

Prompt Engineering as Code: You treat prompts as production code—versioned, tested, and optimized for deterministic outcomes.

  • MCP Expertise: You understand the future of data grounding and have experimented with or implemented Model Context Protocol servers.
  • Growth Agility: You stay ahead of the curve, moving fluently from RAG-based architectures to Long-Context model strategies as the landscape shifts.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:

  • Immediate medical, dental, vision and prescription drug coverage
  • Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
  • Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
  • Vehicle discount program for employees and family members and management leases
  • Tuition assistance
  • Established and active employee resource groups
  • Paid time off for individual and team community service
  • A generous schedule of paid holidays, including the week between Christmas and New Year's Day
  • Paid time off and the option to purchase additional vacation time.
  • For a detailed look at our benefits, click here: https://fordcareers.co/GSR

This position ranges from salary grade 7-8 and ranges from $99,600-$192,900.

Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.

Visa sponsorship is not available for this position.

Relocation assistance IS provided for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

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