Available for collaboration

Yanye Tang

Full-Stack Application Engineer

I design and build modern web applications enhanced by AI systems, focusing on practical architecture, developer efficiency, and real-world usability.

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Core Focus

  • AI-powered web applications
  • Modern full-stack architecture
  • Production deployment workflows
  • Continuous learning through experimentation

About

I build practical software systems enhanced by AI, combining frontend craftsmanship with backend architectural thinking.

I am an engineer focused on building practical software systems enhanced by AI.

My approach combines strong frontend engineering foundations, backend architectural thinking, and curiosity about emerging AI capabilities.

I am particularly interested in the intersection of modern web frameworks, applied machine intelligence, and real-world product delivery.

Featured Work

Selected projects focused on architecture decisions, tradeoffs, and production-oriented outcomes.

AI RAG Chatbot

AI Application Engineer

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A sophisticated Retrieval-Augmented Generation system that grounds AI responses in specific document sets to eliminate hallucinations.

  • Semantic search retrieval
  • Vector database orchestration
  • Multi-document context management
Next.jsTypeScriptVector DatabasesLLM APIs

Portfolio Platform

Full-Stack Engineer

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A performance-first engineering portfolio built with modern rendering strategies.

  • Hybrid rendering decisions
  • Component-driven architecture
  • Continuous deployment workflow
Next.jsTailwind CSSTypeScriptVercel

Full-Stack Ecommerce Management System

Full-Stack Engineer

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A production-ready administrative dashboard and REST API for e-commerce operations, featuring fine-grained RBAC and bot protection.

  • Granular permission-based access control
  • JWT authentication with Argon2id hashing
  • Cloudflare Turnstile bot protection for mutations
React 19NestJSMongoDBTailwind CSSTypeScript

Engineering Capabilities

How I approach AI applications, frontend systems, backend architecture, and delivery workflows.

AI Applications

  • RAG architecture fundamentals
  • LLM API integration
  • Prompt engineering workflows
  • Evaluation-driven iteration

Frontend Systems

  • Component architecture
  • Performance optimization
  • Accessibility awareness
  • Modern React ecosystem

Backend & API Design

  • Authentication flows
  • REST API modeling
  • Security-first mindset
  • Data modeling principles

Delivery & DevOps

  • Deployment automation
  • Environment management
  • CI/CD awareness
  • Production debugging

Engineering Notes

A public notebook for documenting system decisions, deployment lessons, and engineering tradeoffs.

AI Experiments

A dedicated space for rapid experimentation across prompts, retrieval patterns, agent workflows, and evaluation methods.

Now

What I am currently focused on and where I am aiming next.

Currently

  • • Building practical RAG systems for AI Chatbots
  • • Studying evaluation techniques for LLM outputs
  • • Improving system design and production readiness

Interests

  • • AI Application Engineering roles
  • • Developer tooling powered by AI
  • • Intelligent web platforms

Contact

If you're interested in collaboration, engineering discussion, or opportunities, let's build something interesting together.