Shiv Yadav · Frontend Product Engineer

Frontend Product Engineer building scalable React, Vue, and React Native applications.

I specialize in performance optimization, clean architecture, and integrating AI-powered capabilities into production-ready products for global teams.

View Case StudiesDownload Resume
View:

Selected Case Studies

A closer look at how I approach real-world frontend problems in production environments.

Joyride — Urban Mobility Platform (Canada)

Frontend Tech Lead

Joyride is a large-scale urban mobility platform serving users across multiple Canadian cities, with real-time tracking and high concurrency requirements.

Problem

  • •Legacy frontend causing slow initial load times
  • •Poor scalability during peak usage
  • •Inconsistent UI patterns across features

What I Did

  • •Led migration from legacy stack to React
  • •Designed a reusable component architecture
  • •Optimized Core Web Vitals through code-splitting and caching
  • •Improved accessibility to meet WCAG standards

AI Integration

  • •Integrated AI-assisted logic to improve route recommendations and ETA accuracy
  • •Used AI-powered insights to analyze user behavior and optimize key UX flows
  • •Leveraged AI tooling to speed up performance analysis and feature iteration

EatClub — Workplace Food Ordering Platform

React Native Engineer

EatClub is a high-traffic food ordering platform used by corporate employees for daily and scheduled meal ordering.

Problem

  • •Complex ordering flows with high failure sensitivity
  • •Need for real-time order status updates
  • •Performance issues affecting Time to Interactive

What I Did

  • •Built React Native application with optimized navigation flows
  • •Implemented real-time order tracking using WebSockets
  • •Reduced unnecessary re-renders using memoization techniques
  • •Designed scalable state management for order workflows

AI Integration

  • •Implemented AI-assisted menu search and recommendation experiences
  • •Used AI-driven insights to analyze ordering patterns and improve UX flows
  • •Leveraged AI tools to accelerate debugging and reduce iteration time

AI in Practice

How I use AI to improve product experiences, decision-making, and developer productivity in real-world applications.

AI for User Experience

  • • AI-assisted search and recommendation flows
  • • Intelligent data presentation in real-time applications
  • • UX improvements driven by AI-powered insights

AI for Product & Performance

  • • Using AI insights to guide feature prioritization
  • • AI-assisted analysis of user behavior and system metrics
  • • Experimentation with AI-powered automation in workflows

AI for Developer Productivity

  • • AI-assisted coding, refactoring, and debugging
  • • Faster prototyping and iteration using AI tooling
  • • Improving delivery speed without sacrificing quality

Capabilities

Technologies and practices I use to build reliable, production-ready applications.

Frontend Engineering

  • • React, Next.js, React Native
  • • Component-driven architecture
  • • Performance optimization & Core Web Vitals

State & Data

  • • Redux, Context API, async workflows
  • • API integration & intelligent caching
  • • Real-time data handling (WebSockets)

Quality & Delivery

  • • Unit & integration testing (Jest, RTL)
  • • CI/CD pipelines & release automation
  • • Code reviews & team standards

Platform & UX

  • • Web & mobile application development
  • • Accessibility (WCAG-aligned)
  • • Responsive & internationalized interfaces