Vijeth Moudgalya

About Vijeth Moudgalya

I design and build enterprise-grade AI systems that bridge classical machine learning with the new frontier of Generative AI and Agentic Intelligence. My work spans from building predictive models and end-to-end ML pipelines to architecting autonomous multi-agent ecosystems powered by LLMs, RAG, and Model Context Protocol (MCP), A2A (Agent 2 Agent) Protocol.At Deloitte, I’m leading the development of an Agentic AI Audit Assistant within the Omnia platform — a large-scale system that integrates LangGraph, CrewAI, Unsloth AI, and MCP to automate complex audit workflows. This solution has delivered ~45% reduction in manual review time and ~30% improvement in decision accuracy, proving the impact of intelligent agentic systems in enterprise operations.Previously, I worked on classical ML and data science applications including forecasting, NLP-based classification, clustering, and anomaly detection — optimizing operations and reducing incident resolution time by over 40%. My foundation spans Python, TensorFlow, PyTorch, Scikit-learn, and full MLOps pipelines (Docker, MLflow, CI/CD, AWS/GCP).I’m deeply focused on fine-tuning LLMs, building RAG architectures, and exploring autonomous AI agents, memory-augmented cognition, and AI governance frameworks. My goal is to engineer AI systems that can reason, plan, and act — transforming enterprise intelligence at scale. Always open to collaborating on cutting-edge AI initiatives in LLMs, agentic systems, AI infra, and enterprise GenAI transformation.

Experience

1. Senior Data Scientist

   Deloitte

   Apr 2026 — Present

Education

• Jain (Deemed-to-be University)

  Master of Business Administration - MBA, Information Technology Management

• Visvesvaraya Technological University

  Bachelor of Engineering - BE, Computer Science

• BITS Pilani Work Integrated Learning Programmes

  Master of Technology - MTech, Artificial Intelligence and Machine Learning