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Build what you wish existed.

Md Meraj Alam

SDE Intern @ Amazon • full-stack developer

I build resilient, high-throughput software. As a CS undergrad and Amazon SDE Intern, I work across backend microservices, AWS cloud infrastructure (CDK, ECS), and full-stack React applications. Whether designing deployment frameworks or executing zero-downtime architectural modernizations, I focus on low-latency systems, clean design, and shipping results at scale.

Professional Experience

A

Amazon

Software Development Engineer Intern

Jan 2026 – June 2026

  • •Designed and built a scalable AWS AppConfig-based launch management framework that replaced Weblab-driven marketplace rollouts, enabling configuration-only onboarding of new marketplaces, eliminating code deployments for launches, reducing launch lead time from weeks to hours, and removing 25µs p99 checkout latency.
  • •Migrated the Delivery Signal Recommendation Service from HEX (EC2) to AWS ECS Fargate, architecting the complete cloud infrastructure with AWS CDK — container orchestration, load balancing, TLS re-encryption, PrivateLink connectivity, metrics/logging, auto-scaling, and cross-account DNS management.
  • •Built a dedicated AWS CDK-based DNS management platform and deployment pipeline for centralized DNS ownership and cross-account delegation across Prod and Non-Prod accounts, executing a zero-downtime production migration while reducing infrastructure costs by 20%.

Proof of Work

Naano — B2B LinkedIn Creator Marketplace project cover

A pixel-faithful rebuild of the Naano marketing site into a clean, modern Next.js + TypeScript codebase.

Next.js
TypeScript
Tailwind CSS
shadcn/ui
Supabase
Event Management Platform project cover

Official hackathon website built with the MERN stack — scaled to 2000+ participants and 100+ verified certificates.

React
Node.js
MongoDB
MERN
Krishi Seva: Smart Inventory System project cover

An AI-powered inventory system that uses computer vision to track agricultural stock and send SMS alerts.

Python
OpenCV
YOLOv11
React
Flask
IMDB-Movie Sentiment Analysis project cover

An LSTM model trained on IMDB reviews that classifies text as Positive or Negative, served with a Streamlit UI.

Python
PyTorch
Streamlit

Stack I use

Technologies I work with to build products that solve real problems

JavaScript
JavaScript
TypeScript
TypeScript
Java
Java
Python
Python
SQL
SQL
React.js
React.js
Next.js
Next.js
Express.js
Express.js
Node.js
Node.js
FastAPI
FastAPI
Tailwind CSS
Tailwind CSS
MongoDB
MongoDB
PostgreSQL
PostgreSQL
Redis
Redis
Git
Git
Docker
Docker
CloudFlare
CloudFlare
AWS
AWS
Google Cloud
Google Cloud
JavaScript
JavaScript
TypeScript
TypeScript
Java
Java
Python
Python
SQL
SQL
React.js
React.js
Next.js
Next.js
Express.js
Express.js
Node.js
Node.js
FastAPI
FastAPI
Tailwind CSS
Tailwind CSS
MongoDB
MongoDB
PostgreSQL
PostgreSQL
Redis
Redis
Git
Git
Docker
Docker
CloudFlare
CloudFlare
AWS
AWS
Google Cloud
Google Cloud
JavaScript
JavaScript
TypeScript
TypeScript
Java
Java
Python
Python
SQL
SQL
React.js
React.js
Next.js
Next.js
Express.js
Express.js
Node.js
Node.js
FastAPI
FastAPI
Tailwind CSS
Tailwind CSS
MongoDB
MongoDB
PostgreSQL
PostgreSQL
Redis
Redis
Git
Git
Docker
Docker
CloudFlare
CloudFlare
AWS
AWS
Google Cloud
Google Cloud
JavaScript
JavaScript
TypeScript
TypeScript
Java
Java
Python
Python
SQL
SQL
React.js
React.js
Next.js
Next.js
Express.js
Express.js
Node.js
Node.js
FastAPI
FastAPI
Tailwind CSS
Tailwind CSS
MongoDB
MongoDB
PostgreSQL
PostgreSQL
Redis
Redis
Git
Git
Docker
Docker
CloudFlare
CloudFlare
AWS
AWS
Google Cloud
Google Cloud

If you've read this far, you might be interested in what I do.

Let's connect

Find me on these platforms