·
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.