Description

You will architect and deliver end-to-end LLM-powered applications, agentic workflows, and RAG pipelines for enterprise data.

This role is on-site.

Responsibilities

• Design and implement RAG pipelines using embeddings and vector databases.
• Build multi-step, tool-using agents with planning, execution, and memory capabilities.
• Integrate AI systems with APIs, backend services, and cloud platforms.
• Establish evaluation, reliability, and performance strategies for accuracy, latency, and cost.
• Deploy production-grade backend systems using Python.

Required Skills

• 8+ years of experience with Python and Javascript.
• Strong expertise in LLM application development and prompt engineering.
• Hands-on experience with RAG architectures, embeddings, and vector databases.
• Proficiency in agentic frameworks such as LangChain, LangGraph, or AutoGen.
• Experience building and scaling cloud-based applications with strong system design skills.
• Ability to integrate AI systems with external APIs and backend services.

Key Skills

Education

Any Graduate