Ai Software Engineer Jobs in Michigan (NOW HIRING)

Redefining the future of mobility requires high-integrity data, advanced predictive modeling, and sophisticated marketing analytics. That's where Global Data Insight & Analytics (GDI&A) makes a defining impact. Within our Marketing Analytics team, we translate complex customer journeys, campaign performance, and market dynamics into strategic foresight. We advise leadership on brand health, media optimization, and shifting customer needs-ensuring every marketing decision is grounded in evidence. 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.

• Masters Degree in Computer Science, Information Systems, or a related quantitative field.
• 3+ years of professional experience in Software Engineering or Data Science building scalable production systems.
• 1+ years of hands-on experience designing, training, and deploying complex AI/ML systems in production environments.
• Experience working with Python, Java, JavaScript, or Angular programming languages.
• Experience in building autonomous agents using agent orchestration frameworks such as LangGraph, LangChain, LlamaIndex, or similar technologies.
• Experience implementing tool integration patterns (MCP), agent communication protocols, and AI application observability.
• Experience with vector search, hybrid retrieval architectures, or vector databases (Chroma, Qdrant, Pinecone, pgvector).
• Experience working with GCP services (Vertex AI, Cloud Run, and BigQuery) or similar cloud platforms for deploying scalable AI solutions.
• Strong problem-solving and system design skills with the ability to evaluate competing technical approaches and articulate tradeoffs.
• Solid understanding of data engineering (SQL, Spark, data pipelines) and a strong interest or experience in quantitative marketing concepts like multi-touch attribution, cohort analysis, and predictive customer lifetime value.

Even Better, you may have:

• Experience with semantic technologies, marketing mix modeling (MMM), attribution models, or digital media analytics.
• Experience working with graph databases, Graph-RAG applications, or knowledge graphs.
• Experience with context optimization (prompt compression, "lost-in-the-middle" mitigation).

• 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.

• 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 LangChain, LangGraph, or LlamaIndex 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.