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.