Senior AI & Full Stack Engineer, Corporate Communications
Company: Ford Global
Location: United States (Remote)
Salary: $99.6k - $166.6k per year
Type: Full-time
Remote: Yes
Posted: 2026-08-05
About this role
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 ...