Ryan Teo

Architected and delivered full-stack web applications using React, Next.js, Node.js, and TypeScript, supporting 5+ client projects with active user bases ranging from 5,000–50,000 users. Designed and implemented scalable REST and GraphQL APIs, increasing API throughput by ~30% and reducing error rates by 20%. Partnered with product managers and designers to translate business requirements into production-ready features, reducing rework cycles by 25%. Optimized backend performance through query tuning, Redis caching, and API refactoring, improving average response times by 25–30%. Established CI/CD workflows using GitHub Actions and Docker, cutting deployment time from hours to under 20 minutes and reducing release-related issues by 35%.

Built and enhanced customer-facing dashboards and internal tooling using Vue.js, Nuxt.js, and React, supporting localization workflows for 100+ enterprise customers. Implemented backend services in Node.js and Python, enabling asynchronous processing and reducing job execution latency by ~18%. Refactored frontend architecture into reusable, modular components, decreasing feature development time by 20%. Supported cloud deployments and monitoring on AWS, improving environment stability and reducing production incidents by 15%.

Delivered end-to-end web solutions for 6+ startup and SME clients using React, Angular, Node.js, and PostgreSQL. Engineered reusable UI components and backend modules, accelerating feature delivery across projects by 20–25%. Improved database performance through indexing and query optimization, reducing average API response times by ~20%. Collaborated directly with clients during sprint reviews and technical workshops, contributing to higher customer satisfaction and repeat engagements.

Contributed to the delivery of multiple client-facing web applications using JavaScript, React, Node.js, and PHP, supporting production releases on a bi-weekly cadence. Implemented backend APIs and third-party integrations, improving feature completeness and reducing manual operational steps by 30%. Supported AWS-hosted deployments (EC2, S3) and application monitoring, helping maintain 99%+ service uptime. Automated internal data processing tasks using Python, saving operations teams approximately 8–10 hours per week.