Jun 2024 – May 2025 · 11 mos · Bengaluru, Karnataka, India · On-site

• Managing three core modules (User service, Journeys, and USL); built a specialized 16 member engineering team to drive modernization and
• scalability. Revived the development on two modules running in maintenance mode for last 5 years.
• User Service – Central module handling logins, logouts, user profiles, addresses, preferences, and secure PII storage
• Led design and implementation of DPDP-compliant frameworks for consent management, data export, and automated account deletion
• Proactively drove scalability initiatives during Big Billion Days 2024 to handle peak traffic of 550K QPS, ensuring zero downtime
• Successfully delivered track for approximate geocoding of text-based addresses to lat-long coordinates, enabling near real time discovery
• of Flipkart Minutes (Quick-Commerce) icon on Home Page, in serviceable areas; contributing 20% goodness in Minutes GMV
• Currently driving Address Revamp charter, introducing address auto-switch based on current location for quick commerce while
• optimizing historical address retrieval for standard e-commerce, making sure customer experience is consistent
• Journeys – Event driven state machine management system; responsible for sending 1B+ notifications every day, and handle CRM comms
• like cart abandonment, price drop notifications, welcome journey. Platform enables 5% daily GMV and ~18% daily visits for Flipkart
• Optimized the SLA for price drop journey from 10 hours to 15 minutes during Big Billion Days 2024 by splitting the journeys for high
• moving category vs low moving category products
• Integrated Audience Manager, enabling targeted cohort-based journey execution, optimizing retention and engagement
• Ongoing: Enabling A/B testing to compare performance of workflow variants by leveraging in house A/B testing platform capabilities
• Managing User State Layer system, powering widgets like Continue your search, In your Cart, etc. related to user’s recent interactions

Apr 2023 – Jun 2024 · 1 yr 2 mos

• Leading and managing a team of engineers in the NCMC Acquirer vertical which supports and validates the NCMC Rupay card transactions taking place in the major metro systems including DMRC, Mumbai Metro, Gujarat Metro, etc.
• Took the initiative to scale the NCMC Acquirer system from handling 35k transactions/day to 1.5L transactions/day. The system is capable to handle 5x of the current daily traffic being received.
• Working on building the VISA cards support for the metro and other offline merchants.
• Led the development of an internal tool (DebuGenie) which is an AI based chatbot system to help debug any issues related to transactions in natural language. This tool proved to be a significant game changer for our techops/support team by saving their bandwidth by 75% to investigate and debug issues.

Apr 2021 – Apr 2023 · 2 yrs

• Leading a team of engineers in the Fastag Issuer Vertical which deals with the toll transactions and issuance of new tags to customers.
• SME for the transaction(switch) and the dispute modules which currently handle approx 2.5M transactions a day across various toll & parking plazas and take care of the deduction of money from the customer’s wallet.

Apr 2019 – Apr 2021 · 2 yrs

• Drove the development of the transaction manager module of Fastag Acquirer System, which is responsible for calculating the fare for a toll/parking plaza transaction. The module is responsible for automatically calculating the toll fare for a vehicle based on its vehicle class, performing various legitimacy checks and raising the transaction with NPCI.
• Conceptualized and developed a central common module which is responsible for pushing the custom metrics, request/response logging, etc. in an automated way without writing duplicate code in individual modules.

Jan 2019 – Apr 2019 · 3 mos

• Developed a Scheduler System which triggers jobs based on a schedule and frequency. This project was of great importance as it resolved the main issues of Supply System of Movies which synced various movies and their shows from different providers such as PVR, Wave, etc. This enabled quick and near real time updates from the providers to Paytm Movies Platform.
• Automated the entire Performance Analysis Module and the Reporting systems which used to run the tests in an automated manner and used to send reports to the concerned dev teams.

Jun 2018 – Jan 2019 · 7 mos · Gurgaon, Haryana, India

• Was part of the Storefront Team which renders the main Landing Page of the Paytm and Paytm Mall apps. Normal traffic was around 4K RPS.
• Provided and implemented an efficient solution to handle asynchronous cache refresh for the homepage without increasing the latency on the application. This feature was of importance and was widely appreciated since this helped in flash sales during Diwali Sale without any hassle.
• Migrated out the Storefront service from a bigger composite service to ensure that the Paytm Homepage is always in service.
• Redesigned the architecture for Flyouts on Paytm and Paytm Mall apps which enabled simultaneous updates.

May 2017 – Jun 2018 · 1 yr 1 mo · Gurgaon, India

• Led a team of 3 developers to work on an app named Commonhire, an online coding test platform for recruitment purposes.
• Worked on the feature of sending Reactivation Pushes on the product Melon to get people back on the platform.
• Core member of the development team, responsibilities included new feature development, bugfixes and best coding practices to be followed.

Jun 2016 – May 2017 · 11 mos · Chandigarh Area, India

• - Handled 4 major offerings by Jugnoo - Fresh, Meals, Grocery and Feeds. Worked on Customer App backend and Vendor Panels frontend and backend.

Sep 2015 – Feb 2016 · 5 mos · Noida

• Worked as Front End UI Developer for their business product which is currently under development.
• The project used various technologies of AngularJS Framework for the Front End UI Development.

Jun 2015 – Jul 2015 · 1 mo · Bangalore

• Worked on a project that used the Interoperable Capabilites between OpenGL and OpenCL to minimize the OpenCL kernel execution time for various rendering pipelines and filters.