AI Engineer

AI & LLM Stack: Strong proficiency in Python, SQL, and GenAI frameworks (LangChain, LangGraph, CrewAI, AutoGen).  Agentic Design: Hands-on experience building agents with tool-calling capabilities, memory retention, guardrails, and structured outputs.  Retrieval & Data: Solid understanding of RAG architectures, embedding models, prompt engineering, and vector databases (e.g., Pinecone, Q drant, Chroma, We aviate).

 API & Integration: Experience building REST APIs (e.g., Fast API) and moving data across external APIs and SQL databases.  Cloud & DevOps: Practical experience with Docker, container management, and cloud infrastructure (AWS, Azure, or GCP). Good to Have  3+ years of focused experience building and shipping LLM applications or agents in production settings. Familiarity with AI observability and evaluation tools (e.g., LangSmith, Phoenix, MLflow).

Demonstrable portfolio, open-source contributions, or GitHub projects focused on AI agent development.