AI Response Evaluation & Prompt Optimization
Evaluated and analyzed responses generated by large language models during development of LLM-powered applications. Reviewed AI outputs for accuracy, relevance, and hallucinations while testing Retrieval-Augmented Generation (RAG) pipelines. Categorized responses, refined prompts, and validated outputs to improve the reliability and consistency of AI systems.