Vikrant Vani

Mobile App Developer

Talent

MumbaiMember since 22 April 2026

React NativeFlutterAndroidJavaKotlinTypeScriptCross Platform DevelopmentOffline-first architectureBLoC State ManagementREST API IntegrationMySQLMongoDBAsyncStorageFirebaseSupabaseGitGithubAndroid SDKReact Native CLIFlutter SDKReact.jsFramer MotionNativeWindPythonWeb Scraping

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React NativeFlutterAndroidJavaKotlin

About

Cross-platform mobile developer with hands-on experience shipping Android and iOS applications using React Native, Flutter, and Java/Kotlin. Built production-ready apps covering offline-first architecture, BLoC and async state management, REST API integration, and native push notifications — across both personal and internship projects. Comfortable owning the full development cycle from feature scoping to delivery.

Currently completing B.Tech in IT at MIT ADT University; available for immediate SDE-1 or mobile development internship roles.

Experience

ReactJs Development Intern at CyberProtect Solutions (2025-02 – Present)

Built reusable React.js components and developed mobile-first, responsive interfaces for a production cybersecurity platform.

Built 3+ reusable React.js components with Framer Motion animations, deployed across 3+ platform views to ensure UI consistency on a production cybersecurity platform.
Developed mobile-first, responsive interfaces in React.js, improving cross-device usability for security dashboard features used by security professionals on a live platform.

Android App Development Intern at Prodigy Infotech (2024-06 – 2024-07)

Delivered a complete Android application in Flutter within a 4-week internship timeline with production-quality standards.

Delivered a complete Android application in Flutter within a 4-week internship timeline, meeting all project deadlines with no scope reduction.
Prioritized app features against a strict deadline, making scope trade-off decisions that preserved core functionality and ensured on-time, production-quality delivery.

Web Scraping Intern at Dezignolics (2022-07 – 2022-08)

Automated large-scale data collection using Python and MySQL pipeline with high accuracy.

Automated large-scale data collection using a Python + MySQL pipeline, processing 2,000+ records at 95%+ accuracy and eliminating manual data entry effort.
Optimized extraction and validation logic in the scraping pipeline cutting data processing errors and improving pipeline throughput.