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Quang Ngo

@tquangngo

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Backend-focused software engineer intern building scalable APIs and high-performance systems.

United States

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What I'm looking for

I’m looking for a software engineering role where I can build scalable backend services and performance-focused features. I enjoy systems thinking—caching, async pipelines, and reliable distributed processing—while collaborating to ship measurable improvements.

I’m a Software Engineer Intern at FPT IS, where I develop and scale backend services with Spring Boot, PostgreSQL, REST APIs, and Redis. I’ve supported 50K+ daily requests for 60+ enterprise clients and focused on measurable performance improvements.

I also build responsive UI performance by architecting an asynchronous React pipeline using React Query, accelerating UI rendering by 30%. On the backend, I improved API performance by introducing Redis caching, reducing peak response times by 60%.

Alongside my internship, I support university operations as a Student IT Support Assistant—resolving 120+ incidents to maintain 99% station uptime and reducing lecture downtime through on-site troubleshooting. My projects (Job Prep Platform and MQGo) deepen my interest in systems design, distributed pipelines, and high-throughput reliability.

Experience

Work history, roles, and key accomplishments

Current

Undergraduate Teaching Assistant

Current

Tulane University

Aug 2026 - Present (3 months)

Led weekly computer science labs for 50+ students, achieving a 90% full-score assignment rate by guiding
programming exercises, debugging, and core technical concepts in Python. Conducted 6 hours of weekly office hours to provide coursework assistance and project guidance. Collaborated with faculty to review and refine 10+ lab assignments and curriculum materials.

Python Teaching Data Structures Algorithms Leadership

Software Engineer Intern

FPT IS

May 2026 - Jul 2026 (2 months)

Developed and scaled backend services with Spring Boot, PostgreSQL, REST APIs, and Redis to support 50K+ daily requests from 60+ enterprise clients. Cut peak API response times by 60% through Redis caching strategies, connection pooling, and database query index optimizations. Improved UI rendering speed by 30% by designing an async caching and state-sync data pipeline with React Query.