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.