GenAI Application Development: Design, develop, and deploy LLM-powered applications such as intelligent assistants, document summarization, and workflow automation, using frameworks like LangChain or LlamaIndex and models from providers such as OpenAI, Anthropic, or Azure OpenAI. Retrieval-Augmented Generation (RAG): Architect and implement RAG pipelines using vector databases (e.g., Pinecone, FAISS, pgvector), embedding models, and chunking strategies to ground model outputs in enterprise data.