Senior AI & Full Stack Engineer, Corporate Communications

What you'd actually do

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

Skills

What the JD emphasized

• Production AI Experience
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG) architectures

Other signals

• Integrating Generative AI (GenAI), AI-powered search, and Generative Engine Optimization (GEO) capabilities directly into the FTR platform.
• 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.
• 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.