Description

You will drive the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges.

This role is hybrid.

Responsibilities

• Design and develop multi-agent AI systems using LangGraph for workflow automation and autonomous problem-solving.
• Implement knowledge graphs, vector databases, and RAG techniques to enhance agent reasoning capabilities.
• Develop and optimize agent orchestration workflows using LangGraph, ensuring modularity and scalability.
• Lead AI research in Agentic AI and self-improving agents, prototyping adaptive systems.
• Translate Agentic AI capabilities into enterprise solutions and lead PoC projects to demonstrate business impact.

Required Skills

• 5+ years of hands-on experience with LangGraph and multi-agent AI development.
• Proficiency in LLM orchestration using LangChain, LlamaIndex, and OpenAI Function Calling.
• Expertise in reinforcement learning methodologies, specifically RLHF and RLAIF.
• Experience constructing knowledge graphs and implementing Retrieval-Augmented Generation (RAG).
• Experience deploying AI agents in production environments, specifically on GCP.
• Deep understanding of complex decision-making and AI planning in autonomous systems.

Preferred Skills

• Experience with self-improving AI agent architectures.

Key Skills

Education

Any Graduate