· Expert-level Python development skills, with hands-on experience in at least one web framework such as FastAPI, Django, or Flask.

· Proficient in asynchronous programming in Python, with a strong understanding of event loops, concurrency, and async design patterns.

· Practical experience and understanding of Retrieval-Augmented Generation (RAG), embedding models, and text chunking techniques.

· Demonstrated expertise in prompt engineering, including crafting effective prompts for LLMs and optimizing prompt performance.

· Familiarity with integrating LLMs using APIs (e.g., OpenAI, Anthropic, Hugging Face, Azure Open AI, AWS Bedrock) in production-grade systems.

· Experience with Vector Databases (e.g., Pinecone, FAISS, Chroma, or Qdrant)

· Familiarity with LangChain, LlamaIndex, or similar GenAI orchestration frameworks.