Thirupathi

Thirupathi

Google Agentic Premier League Grand Finale Finalist | AI/ML & GenAI Engineer Building Agentic Systems, RAG Pipelines & Intelligent Backend Solutions

Hyderabad


About

I build software that moves beyond generating answers to solving real problems. My work sits at the intersection of Software Engineering, Generative AI, and Agentic Systems. I’m interested in turning complex workflows into intelligent, reliable applications using AI agents, RAG pipelines, and well-engineered backend systems. I built Audit IQ, an autonomous compliance auditor designed to detect anomalies and streamline investigations, reducing audit processing time by approximately 60%. With FinSmart AI, an AI-powered financial intelligence platform and IJESAT-published research project, I explored RAG-based retrieval, financial document analysis, and more reliable AI-generated insights. My toolkit includes Python, FastAPI, Flask, SQL, PostgreSQL, MongoDB, LangChain, LangGraph, CrewAI, Google Gemini, RAG, multi-agent orchestration, React, Docker, Git, and cloud technologies. I care about more than making AI work: I focus on retrieval quality, data validation, evaluation, error handling, and building systems people can trust. Currently, I work as an Data Analyst at GlobalLogic, bringing a data-quality and analytical mindset to real-world workflows. My journey includes being a Google Cloud Agentic Premier League 2026 Grand Finale Finalist, a Google Agentathon Participate, and a researcher published in IJESAT. At GDG DevFest Hyderabad, I’m here to exchange ideas, learn from ambitious builders, and connect with people turning emerging technology into meaningful products. My goal: Engineer intelligent systems that deliver measurable impact, not just impressive demos.

Skills
Agentic AI
Generative AI (GenAI)
AI Agents
Multi-Agent Systems
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Python
FastAPI
Flask
LangGraph
LangChain
CrewAI
Google Gemini
Prompt Engineering
REST API Development
Backend Engineering
Machine Learning
AI Evaluation
SQL
PostgreSQL
MySQL
MongoDB
React
Docker
Git
GitHub
Workflow Automation
Data Analysis
Data Validation
OCR
Computer Vision
Cloud Technologies
and Problem Solving.
Experience

Data Analyst

Globallogic

Sept 2026 to Present
  • Working as a Data Analyst at GlobalLogic, I focus on data analysis, quality validation, and maintaining the accuracy and reliability of structured datasets. My responsibilities include analyzing high-volume data, identifying inconsistencies, anomalies, and missing information, performing quality checks against defined guidelines, and investigating data exceptions to uncover underlying patterns. I document findings, support issue resolution, and contribute to improving data quality and workflow efficiency while meeting productivity and turnaround requirements. This role strengthens my analytical thinking, problem-solving, SQL, and data-driven decision-making skills while giving me practical experience working with real-world data operations.
Projects

StadiumOps AI — Real-Time Intelligent Stadium Operations

Built an AI-powered stadium operations platform that transforms live venue data into actionable operational intelligence. Features real-time crowd monitoring, zone occupancy analytics, incident tracking, risk alerts, emergency scenario simulation, and a Google Gemini-powered intelligence hub that uses live stadium context to generate situational summaries and recommendations. Designed to help operations teams identify emerging risks and make faster, better-informed decisions during large-scale events.

Next.js
React
TypeScript
Tailwind CSS
Firebase Firestore
Firebase Authentication
Google Gemini 2.5 Flash
Vercel.

FinSmart AI — Agentic Financial Intelligence Platform

Built FinSmart AI, a full-stack financial intelligence platform that combines Generative AI, Retrieval-Augmented Generation (RAG), and multi-agent orchestration to transform complex financial information into actionable insights. Developed a document-aware AI assistant that answers finance queries using contextual retrieval, a market sentiment engine that analyzes financial news, an intelligent budget planner that categorizes expenses from natural language, and a CrewAI-powered stock analysis system coordinating specialized Financial Analyst, Research Analyst, and Investment Advisor agents. Integrated financial data sources, vector search, and LLM-powered analysis to deliver a unified experience for personal finance management and investment research. The project is also associated with my IJESAT-published research in applied AI/ML and software systems.

Python
FastAPI
React
Vite
CrewAI
LangChain
NVIDIA Llama 3.3 70B
DataStax AstraDB
Hugging Face Sentence Transformers
RAG
Multi-Agent Orchestration
Chart.js
yfinance
Financial Datasets API
Marketaux News API.
Education

Bachelor of Engineering in Computer Engineering

Matrusri Engineering College

Oct 2022 to Jun 2026