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AI Software Engineer
Job in
Dearborn, Wayne County, Michigan, 48120, USA
Listed on 2026-06-27
Listing for:
Ford Motor Company
Full Time
position Listed on 2026-06-27
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Backend Developer
Job Description & How to Apply Below
Join us and use your analytical expertise to shape how the world connects with our brand.
We are moving beyond "Chatbots." We are building AI-native applications where LLMs aren't just features-they are the core engine. As an AI-focused Software Engineer in Marketing Enterprise Analytics, you will architect systems where autonomous agents navigate complex marketing business logic, utilize the Model Context Protocol (MCP) to interact with live marketing 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 to revolutionize how Ford optimizes its marketing investments and customer experiences.
We are seeking a Software Engineer / Senior Software Engineer (SG6-SG8) to architect the AI foundation for our marketing analytics platform. You will build autonomous agents and intelligent pipelines that dynamically ingest, govern, and query complex marketing data. Your work will enable marketing teams to effortlessly discover high-value analytics assets, leverage deep customer insights, and continuously optimize campaign ROI through agentic AI.
* Design and Build Agentic Workflows:
Design and build AI-powered applications, agents, and intelligent workflows that improve discovery, recommendation, and analysis of marketing enterprise analytics assets, customer data, and media metrics.
* Architect Autonomous Loops:
Transition from linear "chain" workflows to self-correcting agentic loops using frameworks like Lang Chain, Lang Graph, or Llama Index to automate complex marketing analytics workflows.
* Implement Tool-Use & MCP:
Design and implement robust "tool-calling" capabilities, ensuring LLMs can reliably interact with external marketing APIs, Customer Data Platforms (CDPs), and internal media databases. Build and maintain Model Context Protocol (MCP) servers to bridge the gap between LLMs and our proprietary marketing data silos securely and in real-time.
* Develop High-Concurrency Backends:
Develop asynchronous Python (FastAPI/Flask) or Java (Spring Boot) backend services optimized for long-running AI tasks, marketing attribution modeling, and real-time token streaming.
* Build Streaming Frontends:
Build responsive, stateful UIs in React or Angular that handle complex AI interactions (streaming text, generative UI components, and multi-modal feedback).
* Optimize Advanced RAG Pipelines:
Implement advanced RAG pipelines (re-ranking, query transformation, and embedding optimization) to maximize retrieval precision over vast libraries of marketing assets, creative guidelines, and historical campaign results.
* Establish AI Evals & Observability:
Establish AI Evals to quantify hallucination rates, latency, and cost, leading the shift from "vibes-based" testing to rigorous, automated AI benchmarking.
* Collaborate & Guide:
Collaborate with product managers, marketing experts, and domain stakeholders to translate business needs into technical solutions. Drive architecture decisions, engineering best practices, and operational excellence.
* Design and Build Agentic Workflows:
Design and build AI-powered applications, agents, and intelligent workflows that improve discovery, recommendation, and analysis of marketing enterprise analytics assets, customer data, and media metrics.
* Architect Autonomous Loops:
Transition from linear "chain" workflows to self-correcting agentic loops using frameworks like Lang Chain, Lang Graph, or Llama Index to automate complex marketing analytics workflows.
* Implement Tool-Use & MCP:
Design and implement robust "tool-calling" capabilities, ensuring LLMs can reliably interact with external marketing APIs, Customer Data Platforms (CDPs), and internal media databases. Build and maintain Model Context Protocol (MCP) servers to bridge the gap between LLMs and our proprietary marketing data silos securely and in real-time.
* Develop High-Concurrency Backends:
Develop asynchronous Python (FastAPI/Flask) or Java (Spring Boot) backend services optimized for long-running AI tasks, marketing attribution modeling, and real-time token streaming.
* Build Streaming Frontends:
Build responsive, stateful UIs in React or Angular that handle complex AI interactions (streaming text, generative UI components, and multi-modal feedback).
* Optimize Advanced RAG Pipelines:
Implement advanced RAG pipelines (re-ranking, query transformation, and embedding…
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