Senior AI & Full Stack Engineer, Corporate Communications

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.

Enterprise Technology plays a critical part in shaping the future of mobility. If you’re looking for the chance to leverage advanced technology to redefine the transportation landscape, enhance the customer experience and improve people’s lives, this is the opportunity for you. Join us and challenge your IT expertise and analytical skills to help create vehicles that are as smart as you are.

Ford Motor Company is seeking a Senior AI & Full Stack Engineer within our Corporate Communications team to shape the next generation of intelligent content experiences. In this role, you will have full-stack responsibility for our online publication application, From the Road (FTR), built on Adobe Experience Manager (AEM).
 

You will bridge the gap between web experiences and advanced AI—integrating Generative AI (GenAI), AI-powered search, and Generative Engine Optimization (GEO) capabilities directly into the FTR platform. To establish a deep understanding of our application architecture, you will also actively contribute to core, day-to-day full-stack web development. You will partner closely with cloud architects, AEM platform engineers, and product designers to deliver scalable, AI-first content architectures.

1. AI, GenAI & GEO Engineering

• Build enterprise taxonomies, entity models, and knowledge graphs integrated with AEM to convert static pages into structured, reusable content.
• Develop dynamic schema-generation systems (JSON-LD, Schema.org) to automate content tagging and maximize search engine crawling.
• Design backend AI pipelines using LLMs and RAG to automatically generate article summaries, key facts, and FAQs from editorial content.
• Implement automated testing and evaluation frameworks to measure LLM retrieval accuracy, answer quality, and grounding before production release.
• Execute Generative Engine Optimization (GEO) and technical SEO strategies to optimize content visibility across conversational AI platforms and search engines.

2. Full-Stack & API Development

• Develop robust, scalable backend services and REST/GraphQL APIs using Java or Python.
• Build and maintain high-performance, secure microservices and integration layers supporting AI-powered experiences.
• Develop frontend features and components using React, successfully bridging data from modern AI middleware to the web experience.

3. Enterprise Platform Integration (AEM Ecosystem)

• Partner with enterprise AEM engineering teams to integrate AI capabilities into content repositories, enabling automated metadata enrichment, AI search retrieval, and authoring workflows.

4. DevOps & Cloud Engineering

• Develop and maintain CI/CD pipelines using enterprise-standard tools (e.g., GitHub Actions, Jenkins).
• Implement Infrastructure as Code (Terraform) to deploy scalable AI platforms powered by Google Cloud technologies.
• Support observability, monitoring, operational readiness, and DevSecOps compliance for all deployed AI services.

5. Core Application Development & Agile Execution

• Standard Feature Development: Leverage AEM and React to build scalable features and resolve technical issues, ensuring the day-to-day stability and evolution of the From the Road application.
• Domain Familiarization: Actively contribute to standard application features and bug fixes to build deep, hands-on domain knowledge of the platform's codebase and editorial workflows.
• Cross-Functional Collaboration: Partner closely with business stakeholders, UX/UI designers, and product managers to translate requirements into robust, user-focused, and scalable solutions.
• Agile Integration: Actively participate in all agile ceremonies including daily stand-ups, sprint planning, retrospectives, and backlog refinement to design, develop, and deliver feature implementations within sprint commitments.

Minimum Qualifications:

• 10+ years of professional software engineering experience in full-stack or backend development.
• Production AI Experience: Hands-on experience building and deploying production-grade AI/ML applications, particularly with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures.
• Strong Programming Foundations: High proficiency in Java (t