Description

Design and implement comprehensive Agentic architecture for enterprise-level Generative AI agent development.

Responsibilities

• Architect and deploy Retrieval-Augmented Generation (RAG) systems with efficient data processing, including parsing, chunking, and indexing.
• Integrate knowledge graphs to enhance agent reasoning and context awareness.
• Engineer and optimize prompts for accuracy and reliability in generative outputs.
• Orchestrate multi-agent workflows using modern frameworks.

Required Skills

• 6+ years of professional software engineering experience.
• Strong proficiency in Python.
• Hands-on experience with LangChain and LangGraph for agent development.
• Deep understanding of RAG architectures and vector databases.
• Experience with Model Context Protocol (MCP) or similar standardization layers.
• Proven track record in prompt engineering and LLM integration.

Preferred Skills

• Experience designing enterprise-scale agentic systems.

Key Skills

Education

Any Graduate