- Led development of the What's New Notifications system from scratch, utilizing AWS Lambda, DynamoDB, Secrets Manager to deliver an end-to-end system for the Marketing team to communicate new updates to users.- Reduced the free trial account creation time by ~50% by refactoring the workflow architecture.- Developed CRUD APIs for vendor-client mapping following RESTful principles.

- Implemented several backend and DevOps improvements.- Developed solutions for automatic generation of Daylight Saving Time schedules for all time zones around the world by querying the IANA TimeZone DB.- Implemented automation of EC2 Instances list using Powershell, for use during deployments.

- As a full-stack developer, implemented several frontend bugfixes and features in Celayix's flagship Schedule-Xpress webapp as well as efficient, secure backend functions using AWS Lambda.- Worked on the backend system for the Referrals feature, utilising various AWS features including Lambda, SQS and DynamoDB.- Refactored and optimized background SQS tasks, leading to a reduction in AWS billing costs for the company.

- Led migration of legacy PHP applications to Django.- Developed the customer referrals functionality for the HomeLane website from the ground up.- Reduced database query times by up to 20% by refactoring SQL statements.

- Worked as a developer across backend and mobile.- Implemented efficient, secure backend APIs using Django and Postgres- Developed core front-end features on the Android app using Java and Kotlin- Worked closely with the product, design and customer relations teams to create solutions that provide the best possible end user experience.

- Worked as a developer on Instamojo’s Android app- Developed several features focused on business solutions for small and medium sized enterprises.- Wrote professional, high-quality code following best practices with a focus on application stability and user experience.- Modernized the app using MVVM architecture, Android Jetpack components and migration to Kotlin.

- Developed a Textual Emotion Detection System, based on artificial neural networks, to classify a given text snippet into one of four emotions (Anger, Fear, Joy, Sadness) with an accuracy of up to 85% on test data.- It also includes a mechanism for the user to manually flag incorrect results, based on which the system corrects itself automatically.- In addition, a web API was developed for the system using Flask.

- Developed an Android App for renting out farming equipment.- The app covers both the provider and customer perspectives and provides functionality such as searching for specific equipment based on location.- Developed using Android Studio and IBM Bluemix cloud API.