Career Summary
4 years of full-stack development experience specializing in React ecosystems, UI component libraries with design token systems, microservices architecture, RESTful APIs, and performance optimization using caching and content delivery.
Skilled in end-to-end product development, including design, implementation, testing, monitoring, error tracking, and maintenance.
1+ year experience in AI-integrated application development,deploying large language models(LLMs) on cloud platforms with customized prompt strategies and integrated external tools.
Company
Mosaic Manufacturing
Title
Fullstack Software Engineer
Stack
React, TypeScript, NodeJS, Express, AWS
Location
Toronto, Canada
Duration
Nov 2021 - Present
Overview
As a cornerstone of Team Canvas, my contributions since joining include elevating our codebase with over 95% test coverage, completing two comprehensive UI revamps, and executing numerous view redesigns.
I spearheaded the development of the Canvas Teams feature, released in Summer 2023, now widely adopted by organizations and universities such as World Emblem International, Amazon, BMW, Ryerson University (now Toronto Metropolitan University), Carnegie Mellon University, Hong Kong University, and McMaster.
Results and metrics
Collaborated in the UI/UX redesign of Canvas, the company's core web application. Worked closely with designers, utilizing React, Redux, Styled Components, Figma, and Storybook to build a responsive, cross-device user interface
Led the development of a company-wide UI component library using Vite and Radix UI, featuring a custom design tokens system that improved development efficiency and ensured consistency across all products
Transitioned from JavaScript to TypeScript for enhanced type safety, refactored class components to functional ones, and optimized global state and data flow with Redux for ongoing development
Achieved over 95% test coverage through automated Unit and Visual Regression testing using Jest and React Testing Library; integrated Sentry for real-time error monitoring, significantly improving bug detection and resolution times
Developed interactive D3.js visualizations (bar, pie, line charts) to display 3D printer data and material configurations
Developed backend RESTful APIs using Node.js and Express on Amazon DynamoDB for app features. Utilized Zod for schema type declaration and validation to enhance type safety and prevent type duplications
Utilized AWS API Gateway with Amazon SQS and AWS Lambda for handling concurrent 3D project slicing requests and Amazon S3 for storing and managing large 3D projects. Also developed Single Sign-On (SSO) authentication and Role-Based Access Control (RBAC) with Amazon Cognito for university and corporate clients
AIkie - AI-Integrated Stock Analysis Application
Client
Next.js, React, TypeScript, Tailwind
Server
Prisma ORM, Supabase, PostgreSQL, WebSocket, AWS
AI & Payment & Cache
DeepSeek R1 & V3, Langchain, Stripe, Redis
Authentication
Google & GitHub OAuth
Overview
AIkie is an advanced stock analysis application that integrates AI technology to provide users with deep market insights. Built on the powerful Next.js framework, the platform seamlessly integrates DeepSeek R1 and V3 models, offering real-time stock analysis, market trend predictions, and investment strategy recommendations. By combining various financial data APIs and AI analytical capabilities, AIkie provides investors with a one-stop market intelligence center.
Features & Technologies
Developed a Next.js stock analysis application leveraging SSR capabilities (Server Components & Actions), Prisma ORM, PostgreSQL, and Supabase Auth (OAuth); integrated Stripefor payment processing and subscription management
Deployed customized DeepSeek R1 & V3 models on ByteDance Volcano Engine with tailored knowledge bases, external tools, and prompt strategies; utilized Vercel Analytics, Vercel Insights, and Sentry for monitoring and optimization
Engineered real-time streaming of large language model (LLM) reasoning processes using AWS Lambda edge functions driven by API Gateway for responsive user experience
Implemented Redis caching strategies with tailored expiry policies for high-frequency financial data, significantly reducing API latency and external request overhead
Utilized Langchain to build financial data processing pipelines, extracting and analyzing market trends, company reports, and relevant news, providing users with comprehensive stock insights
Implemented real-time stock data updates and immediate delivery of AI analysis results through WebSocket, ensuring users have access to the latest market dynamics
Employed Zod for comprehensive type-safe data validation, ensuring accuracy and consistency of financial data
Managed application state efficiently with Zustand, providing a lightweight and flexible state solution for complex stock filtering, comparison, and tracking features
