Ranjithragavan

Building autonomous, stateful AI ecosystems that bridge enterprise systems with next-gen Agentic Workflows. Focusing on high-performance orchestration using LangGraph and Google ADK.

Top Skills

Agentic AI Development

Designing autonomous agents that exhibit intent and independent decision-making.

Multi-agent AI Systems

Orchestrating complex workflows where multiple agents collaborate to solve enterprise challenges.

LangGraph

Building stateful, cyclic reasoning graphs for robust and persistent AI workflows.

Model Context Protocol (MCP)

Implementing standardized protocols to connect LLMs with local and remote data tools.

Retrieval-Augmented Generation (RAG)

Optimizing high-precision retrieval using vector databases like Chroma and Qdrant.

Professional Experience

2024 — PRESENT

Technology Lead @ Infosys

Architecting Multi-Agent systems for enterprise ITOps. Hands-on development of POCs focusing on tool-calling latency and state-persistence across workflows. Managing deployments across GCP Vertex AI, AWS Bedrock, and Azure AI Foundry.

LangGraph Google ADK MCP Servers Python
2022 — 2024

Technology Analyst

Transitioned from data engineering to AI, focusing on RAG pipelines and NLP for backend systems. Utilized PEFT for model fine-tuning and managed backend deployments.

Chroma Qdrant PEFT Oracle SQL

Academic Publication

BIT JOURNAL

Neural Networks in Biotechnology

Published research on increasing Spirulina platensis productivity using artificial neural network modeling.

View Paper →