AI Prompt Engineer, DataMind Technologies
Engineered and iterated 300+ production prompts for customer support, content generation, and data extraction workflows using LLMs. Built RAG-based prompt grounding to improve factuality and decrease hallucinations by linking outputs to proprietary knowledge bases. Created a structured prompt evaluation framework using automatic metrics to systematically validate prompt quality and reduce QA turnaround time. • Designed few-shot and instruction-based prompt variants • Implemented RAG pipeline with LangChain and Pinecone for knowledge grounding • Evaluated prompt effectiveness using BLEU, ROUGE, and G-Eval • Collaborated with ML engineers and PMs to translate requirements into prompt specifications