# William Wang

Software engineer & AI enthusiast

- Email: william.mq.wang@gmail.com
- GitHub: https://github.com/William-AIdev
- LinkedIn: https://www.linkedin.com/in/william-mq-wang/

## Profile

Backend-leaning software engineer with hands-on experience in API development, system automation, full-stack delivery, and AI-powered workflows. Strong in Python and SQL, comfortable owning backend architecture while collaborating across frontend and product boundaries. Completed an internship in Australia, with a focus on practical, production-ready systems.

## Selected Experience

### AI Agent & System Design — Personal Project

Repository: https://github.com/William-AIdev/Agentic-RentingSystem

- Designed and implemented an AI-powered rental order assistant using LangGraph and LLM APIs, supporting end-to-end order workflows.
- Built a rule-based RAG system with Markdown document chunking, HuggingFace embeddings, and vector database retrieval.
- Optimised tool-calling flows and token usage through structured agent design and iterative evaluation.
- Containerised the system with Docker Compose and integrated CI pipelines for reproducible deployment and code quality.

### Full-Stack Project Delivery — University & Personal Projects

- Led frontend implementation using React, Next.js, and TypeScript, translating self-designed UI prototypes into production-ready interfaces.
- Defined API contracts with backend services and validated integrations to maintain consistent data flow.
- Deployed cloud-ready systems with containerisation, CI/CD pipelines, and environment separation.

## Education

Master of Information Technology — UNSW

## Core Skills

- **Languages:** Python, SQL, JavaScript, Bash
- **Backend & systems:** RESTful API, OpenAPI, Authentication & RBAC, PostgreSQL, SQLAlchemy, Supabase
- **Frontend:** React, Next.js, TypeScript, Tailwind, Figma-to-Code
- **AI & automation:** LangGraph, LangChain, RAG, vector databases, workflow automation, LLM tool calling
- **DevOps & engineering:** Docker, CI/CD, GitHub Actions, Linux, cloud-ready architecture

## How I Work

Project-level thinking with attention to user experience. A fast learner across new frameworks, with a preference for clean abstractions, tests, and maintainable architecture.

## Exploring Next

AI-augmented business workflows, agent-based systems, and automation that reduces operational effort. Continuing to go deeper into DevOps.