A comparison table titled "AI FDE vs. Traditional FDE" detailing differences in the job descriptions across six dimensions. For Core Technology, Traditional FDE focuses on platform configuration and data integration while AI FDE focuses on LLM deployment, RAG systems and fine-tuning. Technical Depth for Traditional is full-stack and data engineering compared to AI’s full-stack, ML/AI and data science. Evaluation moves from system performance and user adoption to model quality, hallucination detection and evals. Optimization Focus shifts from query performance and data pipelines to inference latency, token costs and prompt engineering. Cutting-Edge Exposure involves established technologies for Traditional and frontier models and research breakthroughs for AI. Finally, Uncertainty Level is characterized by defined solutions and proven patterns for Traditional FDE while AI FDE deals with "Ambiguity is the default" and emerging best practices.