Resume

2026-04-03

Kenneth Ong Kuan Phing 王關平

Full Stack Engineer | github.com/kennethong02 | linkedin.com/in/kenneth-kuan-phing-ong

Experience

Full Stack Engineer · WisdomGarden Taiwan Ltd (台灣智園有限公司)

August 2025 – Present · Taipei, Taiwan

  • Architected and delivered key features for a Learning Management System (LMS) using Next.js and TypeScript, achieving a 30% performance improvement over the legacy platform.
  • Collaborated with cross-functional teams to define technical requirements, prioritize features, and maintain sprint velocity.
  • Built RESTful APIs with Python to support data-intensive LMS workflows, improving backend reliability and reducing response latency.
  • Tech stack: Next.js · TypeScript · Python

Software Engineering Intern · Taipei Exchange

July 2024 – August 2024 · Taipei, Taiwan

  • Engineered a FIX financial trading server using the QuickFIX/C++ library, enabling real-time order routing in compliance with FIX protocol standards.
  • Designed and executed multithreaded load tests, identifying and resolving bottlenecks that increased system throughput by 20%.
  • Gained hands-on experience in low-latency systems, financial protocols, and production-grade C++ development.
  • Tech stack: C++ · QuickFIX · FIX Protocol

Skills

Programming Languages: C/C++ · Python · JavaScript · TypeScript · Dart · Bash · HTML · CSS Frontend: React.js · Next.js · SvelteKit · Flutter · Vite Backend: Django · Flask · Spring Boot · Node.js Databases: MySQL · Firebase · Supabase Tools & DevOps: Git · Docker · Podman · Vercel · Vitest Languages: English (TOEIC 930) · Mandarin · Malay

Education

Exchange Student — Dept. of Information Technology · Uppsala University

September 2024 – August 2025 · Uppsala, Sweden

B.S. in Computer Science and Information Engineering · National Taiwan Normal University

September 2021 – August 2025 · Taipei, Taiwan

Projects

Personal Portfolio & RAG-Powered Knowledge Chat

Designed and built a personal website with an AI-powered chat interface over my Obsidian note vault using Retrieval-Augmented Generation (RAG). The frontend is a SvelteKit static site deployed on GitHub Pages; the backend API runs on Vercel with pgvector on Supabase for semantic vector search. Enables natural language queries across hundreds of personal notes with high relevance.

Tech stack: SvelteKit · Vercel · Supabase · OpenAI API

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