back-end | front-end
| machine learning

I'm a Bangalore based software engineer who is an expert in building modern cloud based applications using Nodejs, Javascript and Python in the backend, the frontend and for machine learning.


Sorted Image

As the tech lead for Sorted, I built the entire backend stack using Golang inside Docker as the API service and MQTT on Erlang for the communication service. The database used was MySQL.

The mobile application design was initially handled by a colleague until the backend was complete post which it became a collaboration to get the functionality built with some native modules mixed in.


  • OTP User Authentication
  • Groups Chats
  • One-to-One Messaging
  • Push Messages using FCM
  • Support for text, image, calendar and poll messages

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TinCan Image

As the Web Technologies Lead Engineer, I developed plugins and resuable libraries for the web app as well as the mobile app to according to the needs of the business and development team.

I also developed experimental libraries using the bleeding edge HTML5 voice technology available at the time and first dipped my toes into the world of automation by automating testing for that library to check compatibility across multiple browsers running on multiple devices.

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Bhāsha Bandhu

Bhāsha Bandhu Image

As the tech lead for Bhāsha Bandhu, I managed two trainee engineers and three data entry operators during the entire development process. The entire application is built using PHP and MySQL for the backend server and with Cordova and AngularJS for the app & administration frontend.

Bhāsha Bandhu is an e-learning app developed for an NGO. It was engineered with the constraint of deployment in areas with poor or no working internet. The features we enabled the app with to deal with this constraint are as follows:

  • Ability to work offline
  • Support for multiple users
  • Modular content that can be downloaded with support for pause & resume
  • New functionality available without needing to update the app
  • Metrics collection for better analytics of usage adoption & study patterns

This app won an award at a local tech competition.

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Trapigo Image

Trapigo is a food delivery application which allows for the easy tracking of food orders. As the lead Android engineer for Trapigo, I built the entire app using Kotlin. The design of the application was provided by a professional designer and I was responsible for implementing it to pixel perfection in code.

I also worked with a backend engineer to integrate his APIs into the app to build functionality as per the client's requirements.

Some of the features built into the application are:

  • A background service that receives new orders for the user to accept / reject
  • A time limit to accept new orders before they are deferred to another user
  • A GPS tracking service that regularly updates the backend with the user's position
  • A kill switch for the services for when the user goes off duty

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ChristCode Image

An online clue solving competition that is designed to make students learn more about the world while allowing them to compete with their friends. It uses a system of vague questions and clues to help players discover the world by connecting the dots during the search process. It evolved into a basic AI that used text mining to learn things about players.

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StudyAlley Image

A cloud based LMS that integrates data analytics to show where students are struggling in their course. It uses an anonymous feedback based system for teachers to improve classes on the fly as well as various features for improving the communication process throughout the department.

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