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ming-x-yue/README.md

Hi there 👋 I'm Ming Xuan Yue

I’m a Software Engineering student at McGill University with a strong interest in backend development and applied AI systems.
I enjoy building reliable AI solutions that combine LLMs, RAG retrieval and backend engineering to solve real business problems.

Currently, I’m working as a Backend AI Developer Intern at Ciena, where I focus on improving the reliability and evaluation of multi-agent RAG systems used for cloud emulation portal.


🛠️ Technical Skills

Programming & Backend

  • Python, Java, TypeScript
  • FastAPI (async), REST APIs
  • Git, Docker

AI / Machine Learning

  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Multi-agent systems & agent orchestration
  • Prompt engineering & tool calling
  • LLM evaluation (LLM-as-a-Judge)

Data & Analytics

  • Pandas, NumPy
  • Data preprocessing & analysis
  • Performance metrics & benchmarking

Cloud & Tools

  • Azure / OpenAI APIs
  • Jupyter Notebook

🤖 Featured Projects

🔹 Multi-Agent RAG AI Assistant (Enterprise)

Tech: Python, FastAPI, LLMs, RAG, async programming

  • Designed and improved a multi-agent RAG pipeline for internal documentation search
  • Reduced answer inconsistency using agent memory and noise filtering
  • Implemented agent orchestration (preprocessing, tool calling, sub-agent routing, post-processing)
  • Built automated evaluation using LLM-as-a-Judge and performance metrics

➡️ Private enterprise project — architecture and learnings documented

Software Developer Intern

  • Built a RAG-powered enterprise chatbot using LangChain and Dify, integrating with a MySQL database to retrieve customer business data and reduce manual workload for client success and strategy teams.
  • Designed an AI workflow automation system using LLMs to generate image prompts and marketing strategy prompts from keywords and visual inputs, accelerating content creation for marketing teams.

🚀 Projects

Fitness Center Management Website — Full Stack

Tech: Java, Spring Boot, MVC, REST APIs

  • Collaborated in a 5-member team to build a fitness center management platform using a layered MVC architecture with Spring Boot.
  • Applied dependency injection and inversion of control to decouple components, improving maintainability and extensibility.
  • Designed RESTful APIs with structured exception handling and request/response DTOs to ensure clean frontend–backend communication.

Fred (Financial Planning & Budget Tracking System) — Full Stack

Tech: Node.js, Prisma, PostgreSQL, REST APIs

  • Collaborated in a 7-member agile team following Scrum methodology with 2-week sprints and daily stand-ups; served as Scrum Master to coordinate progress.
  • Architected backend infrastructure using Node.js and Prisma ORM with a PostgreSQL database, implementing secure RESTful APIs for financial data management.
  • Ensured ACID compliance for all financial transactions and supported real-time budget calculations.

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