ALISH KUMAR

Led the development of the BluSmart Charging App using SwiftUI, Combine, and a MVVM architecture, maintaining a 99.9% crash-free experience.

Developed and delivered key features in the BluSmart Rider App, including a server-driven Help section, dynamic Home Screen, and real-time Ongoing Ride Screen - enhancing scalability, user experience, and feature flexibility.

Migrated from Storyboard to fully programmatic UI (coded layout) to enable dynamic and flexible Ul management.

Refactored legacy RideDto from a Dictionary-based model to a strongly typed Swift struct, improving code safety and readability.

Integrated MoEngage events to track user behavior and support personalized engagement strategies.

Implemented a consistent and reusable Navigation Header across all screens, along with enabling the interactive back swipe gesture for seamless and intuitive navigation - enhancing overall UI/UX consistency.

Integrated a barcode scanner using AVFoundation to scan charger QR codes, enabling quick and reliable charger identification within the app.

Refactored legacy code to reduce app bundle size, enhance performance, and cut load times by 50%, delivering a significantly faster and more efficient user experience.

Optimized memory and performance by identifying and fixing leaks, improving app stability and boosting efficiency by 20%.

Led the development of BluSmart Rider, BluSmart Charging, and BluSmart Hub Android apps, building each from scratch using Kotlin, DataBinding, and Coroutines.

Followed MVVM architecture for clean, maintainable, and testable code in all projects.

Integrated APIs across all three apps, ensuring seamless data flow and efficient back-end communication.

Utilized Hilt for dependency injection in the Charging and Hub apps, ensuring efficient and scalable code architecture.

Developed and maintained the Golfication Android app, enhancing performance and user experience.

Developed a stats visualization feature for golf players using Google Maps and MPAndroidChart, allowing users to view their performance data and compare it with other players.

Supported three scoring modes Classic, RangeFinder, and GPS-based Advanced Scoring - enabling flexibility based on player preferences and available tech.