Currently focusing on building next-generation Agentic AI systems, specialising in creating scalable agentic frameworks and implementing RAG architectures. Passionate about bridging the gap between theoretical AI research and practical business applications.

• AI Engineering expertise with hands-on experience in advanced frameworks like CrewAI, LangGraph, LlamaIndex and AutoGen
• Production-grade RAG systems development with sophisticated retrieval mechanisms
• Enterprise systems knowledge from 3+ years as an SAP professional, bringing unique technical breadth
• MSc in Applied Data Science with proven ability to translate academic concepts into business value

Created a multi-file conversational Q&A system that processes 50+ document types with 2× faster parsing than traditional approaches. Enhanced context management through custom indexing strategies, delivering 60% productivity gains for knowledge workers.

Developed a cross-database SQL assistant using transformer models and chain-of-thought prompting, reducing data retrieval time by 80% and achieving 70% higher accuracy for business users without SQL knowledge.

Engineered an autonomous research assistant utilizing multi-agent architecture that reduced search time by 90%, featuring URL-specific knowledge extraction and context-aware conversation management.

• MSc in Applied Data Science (Merit) - University of Central Lancashire, UK (2023)
• BE in Computer Science (Merit) - Rajalakshmi Engineering College, India (2019)
• Published in Springer - "Sensible Autonomous Machine Using Deep Learning and CNNs" (2020)

Before transitioning to AI engineering, I spent 3+ years at Tata Consultancy Services optimizing enterprise systems, where I:

• Reduced SAP upgrade times by 30% while maintaining system integrity
• Managed 100+ monthly system upgrades across multiple environments
• Maintained 99% customer satisfaction across critical infrastructure