Description

You will build and optimize LLM-driven systems using RAG patterns and cloud infrastructure.

Responsibilities

• Design and deploy LLM-driven RAG workflows using LangChain and vector databases.
• Integrate and manage vector databases for high-speed vector searches and data retrieval.
• Build APIs with FastAPI and Uvicorn to support low-latency, high-traffic interactions.
• Use AWS services like Lambda and ECS to build scalable, serverless containerized applications.
• Implement observability practices using Datadog and ddtrace to monitor complex workflows.

Required Skills

• 7+ years of professional experience.
• Proficiency in LLM and RAG workflow development, including LangChain and vector databases.
• Advanced Python skills (>=3.11, <3.12) with asynchronous programming experience.
• Expertise in the AWS environment, including Lambda and ECS.
• Experience building and managing containerized environments (Docker).
• Familiarity with building APIs using FastAPI.
• Experience with observability tooling such as Datadog and ddtrace.

Key Skills

Education

Any Graduate