---
title: "RUPESH KUMAR JHA - Senior Software Engineer in Noida | Tal"
description: "Meet RUPESH KUMAR JHA, Senior Software Engineer @ Paytm | Building 100M+ Scale Distributed Systems | Java • Spring Boot • Kafka • Cassandra • Microservices based in Noida. AI stack includes codex, cursor, and claudecode."
image: "https://tal.club/meet/rupesh-kumar-jha/share-image"
---

# RUPESH KUMAR JHA on Tal

## Headline

Senior Software Engineer @ Paytm \| Building 100M\+ Scale Distributed Systems \| Java • Spring Boot • Kafka • Cassandra • Microservices

## About

Backend engineer at Paytm\. I build distributed systems that move money and messages for 100M\+ users every day\. What that looks like in practice: 🔹 Redesigned a notification system from scratch — cut infra cost by 82% \($500/mo → $90/mo\), zero downtime 🔹 Built the central data layer for Paytm's recharge platform — 16 Kafka topics, dual\-store persistence \(Cassandra \+ MySQL\) 🔹 Designed an end\-to\-end SMS parsing system serving 200M users daily 🔹 Modernized a monolithic bill processor into microservices handling 70M\+ records 🔹 Led AI\-driven engineering across 10\+ repos — built an AI deployment orchestrator and MCP server integrations connecting AI agents to Jenkins, Bitbucket, Jira, and Grafana Stack: Java • Spring Boot • Kafka • Cassandra • MySQL • Aerospike • Spark • Hudi • Node\.js • Python What I care about: clean architecture, observability, killing legacy code, and writing systems boring enough to sleep through on\-call\. Lately I'm spending a lot of time at the intersection of backend infra and AI tooling — figuring out how agents can actually be useful inside engineering workflows\. 4 Paytm awards along the way: Rising Star \(Dec'22\) and Rock Star \(Dec'23, Jan'26\)\. Open to chatting with engineers building cool infra, folks working on AI and recruiters with interesting backend roles\. 📩 rupeshjha909@gmail\.com

## Location

Noida

## AI stack

codex

cursor

claudecode

## Work experience

Senior Software Engineer at Paytm, Jul 2024 \- Present · 2 yrs 2 mos, Owning backend infrastructure for Paytm's bill payments and recharge platform — systems serving 100M\+ daily transactions across Java, Spring Boot, Kafka, and Cassandra\. 🔹 Distributed Notification System — 100M\+ daily alerts, 20M\+ users, 99\.9% uptime 🔹 Drop\-Off Reminder Redesign — 82% infra cost reduction \($500 → $90/mo\) 🔹 Recharge Saga Microservice — 16 Kafka topics, dual\-store persistence 🔹 Recharges BFF — sub\-50ms latency with Aerospike caching 🔹 AI\-Powered Engineering Platform — automated deployment orchestrator, MCP integrations across Jenkins, Bitbucket, Jira, Grafana Tech: Java, Spring Boot, Kafka, Cassandra, MySQL, Aerospike, Node\.js, Python, Claude Code, MCP Servers

Software Engineer at Paytm, Jun 2022 \- Jul 2024 · 2 yrs 2 mos, Noida, Uttar Pradesh, India

Software Engineer Intern at Paytm, Jan 2022 \- Jun 2022 · 6 mos, Noida, Uttar Pradesh, India

Data Science Intern at Indian Institute of Technology, Patna, Jun 2021 \- Jul 2021 · 2 mos, Patna, Bihar, India, Project: Data\-Driven Prediction of Battery Cycle Life => Led a project focused on accurately predicting the cycle life of batteries before experiencing capacity degradation\. => Analyzed measurements obtained during a limited number of charging cycles to ascertain battery health and predict its remaining lifespan\. => Developed a methodology to efficiently estimate the number of cycles a battery has undergone and forecast its potential lifespan before reaching a critical state\. => Machine Learning algorithms including K\-Nearest Neighbors \(KNN\), Naïve Bayes, Logistic Regression, Support Vector Machine \(SVM\), Decision Tree, and Random Forest\. => Achieved an exceptional accuracy rate of 97%, showcasing the effectiveness of the chosen methodology and algorithms => Demonstrated the ability to provide accurate cycle life predictions for batteries, enabling proactive maintenance and resource allocation\.

Data Science Intern at The Sparks Foundation, Oct 2020 \- Oct 2020 · 1 mo, => Implemented a Decision Tree Classifier on the well\-known IRIS dataset for multi\-class classification\. => Visualized the decision tree graphically to gain insights into the classification process and improve interpretability\. => Demonstrated the ability to make accurate predictions for new data points based on the trained model\. => Utilized Supervised Machine Learning techniques to predict the percentage of marks for a student based on the number of study hours\. => Developed a Linear Regression model to establish the relationship between study hours and academic performance\. => Achieved accurate predictions, enabling informed decision\-making for educational support and resource allocation\.

## Education

Bachelor of Technology \- BTech, Electronics and Communications Engineering, National Institute of Technology , Patna

Intermediate, PCM, Sri Chaitanya College of Education

[View the original profile](https://tal.club/meet/rupesh-kumar-jha)

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