Source description
About the role
Top Skills: Strong programming experience in Python, Javascript. Strong exp with LangGraph, LangChain, RAG architectures, embeddings, and vector databases. Strong exp with AI systems with APIs, backend services, and cloud platforms.
Responsibilities
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 (planning, execution, memory) using frameworks such as LangChain or LangGraph Integrate AI systems with APIs, backend services, and cloud platforms Establish evaluation, reliability, and performance strategies (accuracy, latency, cost)
Preferred: 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)
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