---
title: "Harsh Vardhan - Software Engineer in India | Tal"
description: "Meet Harsh Vardhan, Software Engineer @ Oppex AI | Ex - EY, Nagarro based in India. AI stack includes claude code, claude, and cursor. Explore public work links including github, leetcode, and harsh-vardhan-portfolio.vercel.app."
image: "https://tal.club/meet/harsh-vardhan-14/share-image"
---

# Harsh Vardhan on Tal

## Headline

Software Engineer @ Oppex AI \| Ex \- EY, Nagarro

## About

• Software Engineer at Oppex AI, owning end\-to\-end features for an AI\-driven incident management platform\. • Translate real customer problems into scalable system designs and implement them across the full engineering lifecycle backend APIs, data modeling, frontend integration, and deployment\. • Actively contributes to improving reliability, performance, and usability through practical AI\-based solutions\. • Previously worked at Ernst & Young, gaining experience with large\-scale enterprise systems and consulting\-led problem solving\. • I started my career at Nagarro, building strong software engineering fundamentals in a global MNC environment\. Currently deepening expertise in backend engineering, system design, and AI engineering concepts, focused on building scalable, real\-world systems\.

## Location

India

## AI stack

claude code

claude

cursor

gemini

github copilot

mcp

## Work experience

Software Engineer at Oppex AI, Jul 2025 \- Present · 1 y 4 mo, Bengaluru, Backend Engineer at Oppex, building scalable incident management, on\-call scheduling, and PagerDuty\-to\-Oppex migration systems\. • 𝗣𝗮𝗴𝗲𝗿𝗗𝘂𝘁𝘆 𝗠𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Migrated enterprise customers from PagerDuty and built daily reconciliation across 13,000\+ incidents/week, achieving \~82% match rate\. Improved title matching, reducing unmatched incidents by 54% to enable confident customer cutovers\. • 𝗔𝗜 𝗢𝗻\-𝗖𝗮𝗹𝗹 𝗣𝗿𝗲𝗽: Built personalized pre\-shift briefs featuring predicted incidents and the top 3 likely causes linked to similar historical incidents\. Integrated TypeSafe’s Jev model to validate causes and lower confidence when uncertain\. Added workspace\-level controls and a platform\-wide kill switch\. Reduced LLM costs by sharing calls across briefs with the same predicted problem and reusing results when evidence remained unchanged\. • 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: Made incident listing 3\.9× faster \(2\.1s → 0\.5s\) for workspaces with 1M\+ incidents through query optimization and indexing\. Added a 1M\-incident benchmark to validate future changes\. • 𝗢𝗻\-𝗖𝗮𝗹𝗹 𝗦𝗰𝗵𝗲𝗱𝘂𝗹𝗶𝗻𝗴: Built rotations, leave and shift\-swap overrides, roster change history, and timezone support\. • 𝗕𝘂𝗹𝗸 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Implemented role\-aware bulk Resolve, Acknowledge, and Snooze\. Reduced database queries for large incident exports from \~500 to 1\. • 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗘𝗿𝗿𝗼𝗿 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻: Built OnCallLogger to scan AWS S3 production logs and automatically raise incidents for backend errors\. • 𝗔𝗹𝗲𝗿𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: Added self\-service alert grouping at rule and workspace levels, plus Slack and email notifications for individual, bulk, and automatic resolutions\. • 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 & 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Built automated end\-to\-end and performance test suites, including a 1M\-incident load test integrated into CI\.

Senior Analyst at EY, May 2024 \- Jul 2025 · 1 yr 3 mos, Noida, • Architected and maintained scalable microservices using Python, FastAPI, and MySQL for EY’s Generative AI Studio, reducing manual SDLC effort by 40%\. • Designed and implemented an AI\-driven pipeline leveraging GPT\-4o and Azure Cognitive Search to parse complex business logic, vectorize inputs and outputs, and retrieve historical results, improving BRD and test case generation accuracy by 23% while reducing manual effort by 60%\. • Developed a real\-time Control Tower Logistics \(CTL\) backend using Spring Boot and engineered anomaly detection logic for in\-transit shipments, reducing incident response time by 11%\. • Implemented SAML\-based Single Sign\-On \(SSO\) integration with Azure AD across internal logistics and AI platforms, enhancing security and reducing authentication failures by 25%\.

Trainee at Nagarro, Mar 2023 \- Oct 2023 · 8 mos, Remote, • Built and optimized scalable backend APIs using Spring Boot and PostgreSQL, improving application performance, reliability, and maintainability\. • Integrated RESTful APIs with frontend applications, enabling seamless data exchange and enhancing user experience across multiple client projects\. • Optimized application state management using TypeScript and Redux Toolkit, streamlining data flow and improving code maintainability\. • Reduced unnecessary component re\-renders through efficient state management and rendering strategies, significantly enhancing application responsiveness and scalability\.

## Education

Bachelor of Technology, Information Technology, Dr\. A\.P\.J\. Abdul Kalam Technical University \(AKTU\), Lucknow

## Public links

- github: https://github\.com/harsh1000\-hub
- leetcode: https://leetcode\.com/user\-19
- harsh\-vardhan\-portfolio\.vercel\.app: https://harsh\-vardhan\-portfolio\.vercel\.app/

[View the original profile](https://tal.club/meet/harsh-vardhan-14)

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