I am a Backend Engineer with a strong interest in system design, concurrency, and scalable backend architecture.
I enjoy building low-level systems to understand how real production services work under load.
- 🔭 Current Focus: Backend systems, caching, concurrency, and performance optimization
- 🧠 Problem Solving: Strong foundation in Data Structures & Algorithms (LeetCode)
- ⚙️ Mindset: Think in terms of latency, throughput, consistency, and fault tolerance
- 🤝 Goal: Software Development Engineer (SDE / Backend) role on a production engineering team
| Area | Technologies |
|---|---|
| Languages | C++, JavaScript (Node.js), Python |
| Backend | Node.js, Express.js, REST APIs |
| Systems | Multithreading, Mutex, Condition Variables |
| Databases | MongoDB, PostgreSQL |
| Caching | Redis, In-memory Stores |
| Concurrency | Thread Pools, Producer–Consumer |
| Dev Tools | Git, Linux, MSYS2, MinGW |
| Testing | Stress Testing, Load Simulation |
Redis-inspired In-Memory Key-Value Store
- Designed a single-threaded command execution model inspired by Redis
- Implemented producer–consumer architecture using:
std::threadstd::mutexstd::condition_variable
- Multiple client threads enqueue commands (
SET,GET,DEL) - A dedicated worker thread processes commands serially
GETimplemented using std::promise / std::future- Stress-tested with 10,000 concurrent requests
- Built and tested on Windows (MSYS2 + MinGW)
Concepts:
Concurrency · Thread Safety · Command Queue · In-Memory Cache · System Design
Automated Announcement Scheduling System
- Built backend services to schedule and trigger announcements
- Implemented cron-based background jobs
- Designed REST APIs for scheduling, execution, and status tracking
- Focused on reliability and idempotent execution
Concepts:
Background Jobs · Scheduling · API Design
Anonymous Review Platform (Backend Focus)
- Designed backend to handle anonymous submissions safely
- Implemented spam protection and rate limiting
- Focused on data integrity and abuse prevention
“I prefer understanding how systems work internally —
before scaling them externally.”
- Optimize correctness before performance
- Prefer simple, predictable designs
- Learn by building from scratch