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Full Stack 2026 Full Stack Developer

MuthoPhoneBD – Smartphone Research, Price Intelligence & Comparison Platform

High-traffic smartphone catalog & comparison ecosystem with automated AI spec scraping, real-time retailer price intelligence, and Next.js 16 SSR.

Technologies & Architecture Stack
Next.js 16React 19TypeScriptTailwind CSS v4Laravel 13PHP 8.4MariaDBRedisDocker
Key Technical Accomplishments
Automated AI Ingestion Pipeline: Chained background queue jobs that scrape device specs, discover local retailer prices, auto-import image galleries, and generate SEO FAQs.
Algorithmic Side-by-Side Comparison Engine: Multi-phone comparison tool computing real-time hardware advantages (display tech, camera MP, battery mAh, charging wattage, price-to-performance ratio).
Multi-Container Dockerized Infrastructure: 6-container production architecture (Next.js standalone, Laravel PHP-FPM, MariaDB, Redis, Queue Worker, Nginx) deployed on Oracle Cloud Ampere A1 ARM64 VPS.
Programmatic SERP SEO & Schema.org: Rich snippets using JSON-LD (ItemList, WebSite, Organization), brand deduplication in SERP titles, and canonical indexation safeguards against duplicate comparison URLs.
Dual Pricing Architecture: Distinguishes between official brand warranties and unofficial grey-market prices across verified local retailers with price history tracking.

Project Screenshots & UI Previews (13)

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Engineering Case Study

Overview

MuthoPhoneBD (muthophonebd.com) is a high-traffic smartphone price intelligence, specifications research, and device comparison portal designed for consumers in Bangladesh. The platform enables buyers to research tech specs, track both official and unofficial market prices across local retailers, and make data-driven buying decisions through automated comparison verdicts.

The platform is engineered as a unified multi-tier ecosystem featuring a Next.js 16 (React 19) web client, a React Native (Expo 57) mobile app, and a robust Laravel 13 REST API powered by Redis queues, MariaDB, and AI background processing.


Problem & Market Friction

  • Fragmented Pricing: The regional smartphone market is split between official brand channels and unofficial grey-market imports, creating significant price confusion for buyers.
  • Comparison Complexity: Consumers struggle to parse complex spec sheets (chipsets, sensor sizes, charging wattages, display PWM) without an objective, algorithmic verdict.
  • Content Maintenance Bottleneck: Manually entering thousands of device specifications, image galleries, and SEO descriptions for rapid phone release cycles is unsustainable.

Architecture & Technical Solution

1. High-Performance Two-Tier Stack

  • Frontend: Next.js 16 App Router using React 19, TypeScript, Tailwind CSS v4, and Recharts for price visualization. Implemented ISR (Incremental Static Regeneration) with 3600s cache windows for lightning-fast sub-second TTFB.
  • Backend API: Modular Laravel 13 API on PHP 8.4-FPM utilizing Sanctum authentication, Spatie role permissions, and Redis for distributed caching and queue brokering.
  • Mobile Companion: Cross-platform mobile app built with React Native, Expo Router, NativeWind, and TanStack React Query.

2. Automated AI Catalog & Scraping Pipeline

  • Designed an asynchronous job-chaining pipeline (PhoneAiTask) orchestrated by Redis queue workers:
    1. ImportPhoneFromUrlJob: Scrapes and normalizes raw hardware specifications from international catalogs.
    2. GeneratePhoneDescriptionJob: Uses LLM APIs to draft concise, human-readable editorial device summaries.
    3. GeneratePhoneFaqJob & GeneratePhoneSeoJob: Generates schema-compliant FAQs and targeted meta keywords.
    4. AutoImportPhoneImagesJob: Pulls, processes, and stores multi-angle phone galleries directly to managed storage.
    5. DiscoverRetailerPricesJob: Scrapes and updates retailer pricing matrices.

3. Algorithmic Phone Comparison Matrix (ComparisonVerdict)

  • Built an automated decision engine comparing up to multiple phones side-by-side.
  • Evaluates key hardware criteria:
    • Battery capacity (mAh) & fast-charging speed (Watts)
    • Display technology (AMOLED vs. LCD, refresh rates)
    • Camera resolution & sensor configurations
    • Price delta between official and grey-market variants
  • Outputs an automated buyer verdict summarizing which phone wins each category and recommending the best value-for-money option.

4. Programmatic SEO Architecture

  • Integrated comprehensive Schema.org JSON-LD structured data (WebSite, Organization, ItemList, SearchAction).
  • Implemented smart SERP title deduplication (e.g., dynamically converting Samsung Galaxy S24 vs Samsung Galaxy S23 into clean, high-CTR Samsung Galaxy S24 vs S23).
  • Built canonical URL whitelisting rules to prevent Google duplicate content penalties across dynamic phone comparison permutations.

5. Dockerized Cloud Infrastructure

  • Multi-container architecture managed via docker-compose.yml (6 services: Nginx reverse proxy, Next.js standalone container, Laravel PHP-FPM, MariaDB 11.2, Redis, and a dedicated queue daemon).
  • Deployed on Oracle Cloud Ampere A1 (ARM64) Ubuntu 24.04 VPS with automated deployment scripts and Cloudflare proxy handling SSL termination and global CDN caching.

Key Metrics & Outcome

  • Full Automation: Automated 90%+ of phone catalog entry tasks, reducing new device publishing time from 30 minutes to under 60 seconds per model.
  • Scalable Performance: Sub-100ms API response times enabled by Redis object caching and Next.js standalone server-side rendering.
  • Cross-Platform Reach: Unified data layer simultaneously powering the web portal and a native Android/iOS mobile application.

Interested in building a similar system?

I am open to full-time engineering roles, backend contracts, and full stack applications with Laravel and Next.js.