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AI Engineer with 1+ years in backend development and AI/ML.
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Aspiring Agentic AI Engineer with 1.5+ years of backend experience at TCS, currently working on a Cisco project in GoLang. Gained hands-on AI exposure through the TCS AI Hackathon, where my team reached the regional and semi-final rounds. Also have strong knowledge of Java backend development and problem-solving.
Atria Institute of Technology, Bengaluru
Computer Science and Engineering · Computer Science and Engineering
August 1, 2020 – June 30, 2024
Tata Consultancy Services
Backend Engineer
February 1, 2025 – Present
India
Electricity Management System
November 1, 2025 – Present
Created a web-based electricity management system to streamline bill processing, consumption tracking, and complaint resolution across customers, administrators, and SMEs. • Implemented a role-based application enabling admins to generate and update bills, customers to monitor usage, and SMEs to manage and resolve service complaints. • Created modular API endpoints for scalability and integrated embeddings for semantic search. • Automated billing and complaint workflows to improve operational efficiency, reduce manual effort, and simplify utility service management. • Designed an intuitive interface for bill management, complaint tracking, and resolution monitoring, contributing to a 40% reduction in administrative overhead.
AI-Driven Multi-Agent Credit Risk Engine
March 1, 2025 – Present
Built a multi-agent GenAI-based credit risk platform to automate loan assessment, fraud checks, and explainable decision support for BFSI workflows. • Engineered an AI-powered credit risk decision engine using FastAPI, LangChain, LangGraph, ChromaDB, and Streamlit to automate loan risk assessment and improve lending workflows. • Developed a multi-agent system for risk scoring, fraud detection, explainability, policy validation, and audit support using RAG-based retrieval. • Integrated semantic search, vector embeddings, and ML models to generate context-aware, explainable credit decisions for BFSI use cases. • Designed scalable APIs, secure authentication, and interactive dashboards for real-time risk visualization and decision support.
Salesforce Certified AI Associate
Salesforce
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a proactive approach to learning and applying new technologies, particularly in the AI domain. The diversity of projects (web development, AI-driven systems) and the stated aspiration to be an 'Agentic AI Engineer' suggest a strong interest in innovation and continuous skill development. The experience at TCS, though short, indicates an ability to work in a structured corporate environment. The Salesforce AI Associate certification further shows a commitment to specialized AI knowledge.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex systems, automate processes, and design scalable solutions. The professional experience at TCS highlights problem-solving, debugging, and cross-functional collaboration skills. These suggest a good operational fit for a role requiring independent work and team interaction.