Andrew Wang

I am a frontend-focused full-stack engineer with 7+ years building scalable, high-performance web applications for enterprise environments. I bridge frontend and backend systems and mentor teams to improve code quality and delivery speed.

At IBM I led a modernization of an internal cloud service portal used by 10,000+ administrators, migrating from legacy stacks to a React + Next.js SPA and cutting page load times by 45% while increasing task completion rates by 25%. I built a reusable component library, standardized state management, and introduced WebSocket-based event streaming and frontend lazy loading to handle large datasets efficiently.

I co-built an AI-powered knowledge search assistant using hybrid BM25+vector retrieval, cross-encoder re-ranking, and retrieval-augmented generation (RAG), owning the Next.js chat/search UI and Node/NestJS orchestration. I reduced p95 latency through caching and batched re-ranking, enforced PII-safe ingestion and RBAC-aware retrieval, and achieved 18–25% ticket deflection and 22% lower average handle time for SRE runbook lookups while passing security review with no critical findings.

I work across TypeScript, React, Next.js, Node.js, Java, Python and Go, and I’m passionate about RAG pipelines, real-time systems and accessible design (WCAG 2.1 AA). I look for opportunities to deliver measurable performance and accessibility improvements on large-scale, mission-critical software while mentoring engineers and improving developer productivity.