Description

>> Design and build production-grade LLM-powered applications and agentic systems

>> Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python

>> Design and implement RAG pipelines over enterprise data using embeddings and vector databases

>> Build multi-step, tool-using agents using frameworks such as LangChain

>> Integrate AI systems with APIs, backend services, and cloud platforms

>> Establish evaluation, reliability, and performance strategies

Requirements:

  >> Strong Python expertise with experience building and deploying production-grade backend systems

>> Hands-on experience developing applications using LLMs, including prompt engineering and orchestration

>> Proven experience with RAG architectures, embeddings, and vector databases

>> Experience with agentic frameworks (e.g., LangChain, LangGraph, AutoGen)

>> Fast API, Python, Micro services, RAG

>> Strong system design skills with experience building and scaling cloud-based applications

Key Skills

Education

Bachelor's degree