Qijun Wan

Architected a secure, multi-tenant RAG platform integrating OpenAI and Pinecone for financial analysts, enabling real-time insights and performance monitoring via system logs. Built full-stack Next.js API routes with PostgreSQL/Prisma and a real-time chat interface using React Hooks and SSE to stream AI responses. Implemented a full CI/CD pipeline with GitHub Actions and Terraform, integrating Jest and Cypress testing to automate provisioning and deployment, reducing manual deployment time by 60%.

Designed and deployed a low-code platform empowering non-technical teams to build data-collection forms and workflows, reducing developer requests by 70%. Developed a centralized ECharts rendering system with a component registry, cutting redundant chart code by 70% and reducing PDF report generation time from 3 minutes to 30 seconds. Implemented a global dark mode and theming system using CSS variables and JavaScript design tokens, improving UI consistency and accessibility. Built a monitoring pipeline with AWS CloudWatch Logs to track API health and P95 latency, achieving over 90% unit test coverage with Vitest and React Testing Library.

Designed and deployed a low-code platform empowering non-technical teams to build data-collection forms and workflows, reducing developer requests by 70%. Developed a centralized ECharts rendering system with a component registry, cutting redundant chart code by 70% and reducing PDF report generation time from 3 minutes to 30 seconds. Implemented a global dark mode and theming system using CSS variables and JavaScript design tokens, improving UI consistency and accessibility. Built a monitoring pipeline with AWS CloudWatch Logs to track API health and P95 latency, achieving over 90% unit test coverage with Vitest and React Testing Library.