• Develop scalable pipelines for text ingestion, cleaning, normalization, and tokenization to support downstream applications. • Architect and maintain robust indexing systems and vector databases for semantic search and retrieval. • Create reusable prompting strategies and lead fine-tuning initiatives for LLMs tailored to business-specific tasks. • Construct dynamic knowledge systems and agentic workflows using LangChain and LangGraph. • Apply VRAG and GraphRAG design patterns to enrich information retrieval and contextual understanding. • Perform benchmark testing and model evaluations to improve accuracy, efficiency, and scalability of NLP systems. • Work closely with engineering, product, and research stakeholders to deliver integrated AI-driven features. • Mentor junior data scientists, guide best practices, and drive innovation across AI projects.