Responsibilities
Design, develop, and deploy AI agents using Large Language Models (LLMs).
Build multi-agent systems for business automation and decision-making.
Develop Retrieval-Augmented Generation (RAG) pipelines.
Integrate AI agents with enterprise applications and APIs.
Create prompt engineering strategies and optimize AI workflows.
Build orchestration pipelines using frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
Monitor AI agent performance, reliability, and security.
Collaborate with product managers, data scientists, and software engineers.
Deploy scalable AI applications on cloud platforms.
Required Skills
Python (Advanced)
Strong understanding of LLMs (OpenAI, Anthropic, Gemini, Llama)
Prompt Engineering
LangChain / LangGraph / CrewAI / AutoGen
RAG Architecture
Vector Databases (Pinecone, Weaviate, Chroma, Milvus, FAISS)
FastAPI or Flask
REST APIs
Docker & Kubernetes
Git and CI/CD
SQL and NoSQL databases
AWS, Azure, or Google Cloud
