Nov 2021 – Apr 2024 · 2 yrs 5 mos · Bengaluru, Karnataka, India

• ➤ SDUI Gojek Pay - Builded Server Driven UI for Gojek Pay App, which reduced app release cycle, powering content from backend.
• ➤ Pin Tokenization System - Designed and builded the pin token system for authenticating user for GoTo (Gojek, GoPay, Tokopedia) org.
• Helped in reducing the pin validation latency by 60% in existing flows.

Apr 2021 – Nov 2021 · 7 mos

• ➤ Solved Auto Insurance Bugs and Other Platform Dependent Bugs. Other responsibilities includes code review, design discussion etc.
• ➤ Client Side Metrics (Analytics System) - In the Auto Insurance Product, we need to get to know about where and why customer is dropping in between journey so that we could target those customer (Product which is Data Driven). We've created system to gather metrics so that we could capture client side events (User Journey, Latency Metrics), it includes journey from requirements gathering to create mechanism to get the metrics, Have created generic solution so that System could be extensible to other Amazon India Payments High Frequency Category (Flights, Bus, Movies, Trains and etc).
• ➤ Builded and launched the Covid Vaccine Finder application (https://getcowinvaccine.in/) in Amazon India Platform (application was launched under Retail Amazon Covid Response Program). Responsibility includes Designing Service and creating client side infrastructure. It was volunteer participation.

Feb 2020 – Mar 2021 · 1 yr 1 mo

• ➤ Builded and launched Auto Insurance solution in Amazon https://www.amazon.in/auto-insurance.
• I was part of Amazon India Payments Team (Boson) to build the auto insurance in amazon system. Amazon was the one of the client and investor of Acko. Responsibility includes creating and managing Payments and Post Payment flow, Order Management Life Cycle, Notifications System and Integration with Downstream services (Amazon Multinational Company) to create shadow order at Global Amazon.
• Solved crucial Bugs and enjoyed building something which could be used by million of customers.
• ➤ Migrated Platform Services to Orchestrator (Elastic Container Service, Docker Management Solution) which result in saving 45% of cost in Production from EC2. Migration includes journey from the Planning to Execution [Faced interesting challenges while migration - less file descriptor, latency minimization, log sending from docker container and others many].

Jul 2018 – Jan 2020 · 1 yr 6 mos · Bangalore, India

• ➤ Manipulation Engine : Problem Statement :- While Scraping the data with the help of DOM Path, We don’t get crisp information, so to derive the crisp information we will have to use the some set of rules.
• Phase I - Rule Based UI, Which capture the events and generate the Spring Expression Language Rules which is executed in run time against the users financial data with robust background written in the Spring which maintain the context of the User’s financial Information.
• Phase II - In this Phase we have provided the Automation of Phase I delivery, Context was whenever the Rules have been generated by the System Analyst so they’ll have to take care of the all the superset of users, they approximately spend 30 mins for the one FI’s fields where we have approximately 50 fields supported in Financial Context.
• We have done the analysis and made rule based engine which basically generates Manipulation Rule by just taking input and output from System Analyst. We have used some classical Dynamic Programming algorithms, custom based algorithm and Business logic to derive the Manipulation Rule.
• Achievement - Earlier System Analyst used to take 30 mins for each fields, this has been done by Manipulation Engine within 30 seconds - 60 seconds with testing of rules.
• Stack Used - React, Java, Elastic Search, Spring-Boot
• ➤ Auto Population - Problem Statement - Some Financial Fields are being derived from others fields and there are XML rules with help of it is done. We will have to parse these rules from the Java Code (Which were in Class Level and If Else Condition).
• We Have used Backtracking Logic to derive the Auto population Rules from the Java Code and Open Source Java Parser to Parse down the Java Code.
• Achievement - We have reduced the help of Financial Analyst to approximately Zero in our Automation of Aggregation Platform.
• Stack Used- Java, Spring-Boot
• And Others are - Locator Library and QIF Parser

Jun 2017 – Jul 2017 · 1 mo · Bengaluru Area, India

• Designed scheme for Database, Developed Dashboard for Admin and contributed in ReapBenefit's Android Application named 'Solve Ninja''.
• G Playstore - https://play.google.com/store/apps/details?id=com.solveninja&hl=en_IN