Backend Engineer | Systems Designer
I build scalable backend architectures, design secure APIs, and optimize performance. I don't just write features—I think in systems, edge cases, and architectural tradeoffs.
I prioritize **Modular Monoliths** or **Microservices** based on scale. I focus on separation of concerns, ensuring business logic is decoupled from infrastructure.
I design **RESTful APIs** with a focus on idempotency, versioning, and secure endpoint standardization. I optimize for low latency and predictable data contracts.
I approach data with **Normalization** for integrity, but implement strategic **Denormalization** or **Caching (Redis)** when performance hot-spots are identified.
I implement **JWT-based Auth**, **RBAC (Role-Based Access Control)**, and input validation to mitigate unauthorized access and injection risks at the architectural level.
I look beyond the ticket. I analyze how a feature impacts cascading services, database load, and system stability.
I write code for the next engineer. I prioritize readability, unit testing, and comprehensive documentation.
Focused on **Automation & Performance**. Developed internal tooling that reduced support processing cycles by 30% and improved response consistency across departments. Contributed to architectural clarity through 50+ peer code reviews.
A full-stack collaboration platform for computer engineering students, designed to handle high-frequency interactions and structured resource sharing.
React Frontend ↔ Java/Spring Boot API ↔ MongoDB. Distributed architecture focused on event-driven state updates.
Chose NoSQL (MongoDB) over RDBMS to optimize for flexible, growing student-generated datasets, trading strict relational mapping for horizontal scalability.
Implemented Layered RBAC at the API level, ensuring that data exposure is restricted even if client-side validation is bypassed.
Implement WebSocket-based real-time document editing and a Redis caching layer for frequent API queries to reduce DB hits by ~40%.
High-stakes bidding platform requiring <1s latency for data synchronization and transaction integrity.
Mobile Client ↔ Event-Driven Backend ↔ Real-time Sync Engine. Orchestrated for concurrent bidding events.
Reduced sync latency to sub-second by optimizing event loops and minimizing serialization overhead between services.
Prioritized Consistency over Availability (CAP theorem) for the bidding engine to prevent race conditions during peak auction moments.
Introduce a service-worker offline-first strategy for unstable mobile connections and implement automated dispute-resolution logic.
I'm always open to new opportunities and collaborations. Feel free to reach out!