JQ
中文

Jingyao Qi Building practical cloud, AI, and software systems.

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I turn coursework and project experience into production-minded systems: LLMOps & AI Governance, cloud automation, real-time apps, and Agentic Workflows.

Contact me View projects
JQ

London, Ontario

andyqi315@gmail.com

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portfolio projects

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MEng expected graduation

About

I am a Computer Science graduate from Western University and MEng student in Electrical and Computer Engineering, Software Engineering stream. My work combines backend development, cloud platforms, DevOps practices, and AI agents — with a strong focus on building projects that solve real-world infrastructure and product challenges.

Focus

Full-Stack Developer

Focus

Agentic Workflows Builder

Focus

Backend Developer

Education

Sept. 2025 — Dec. 2026 (Expected)

Western University

MEng Electrical and Computer Engineering in Software Engineering

London, ON

Sept. 2021 — May 2025

Western University

Bachelor of Science in Computer Science

London, ON

Technical Skills

AI & Data

LangGraphRAGQdrantLlamaIndexLangChainPandas

Languages

JavaPythonC/C++SQLitePostgreSQLJavaScriptHTML/CSSR

Frameworks

ReactNode.jsFlaskSpring BootSocket.IOQt

Cloud & DevOps

AWSGoogle CloudIBM CloudDockerKubernetesAzure DevOpsGrafana

Project Experience

Featured project

CloudOptix

AI FinOps / Cloud Automation · 2026

AI-powered FinOps agent that analyzes AWS EC2 billing and utilization data, retrieves pricing policies through RAG, and generates human-approved cost optimization plans.

  • Built a LangGraph multi-agent workflow for inspection, pricing research, and optimization recommendations.
  • Integrated Qdrant-backed RAG over structured AWS pricing and downgrade policy data.
  • Added safe AWS paths for Cost Explorer import, CloudWatch enrichment, dry-run planning, and human-approved execution. (In progress)
PythonLangGraphRAGQdrantboto3AWS Cost ExplorerCloudWatch
View on GitHub

Stock Microservices

Distributed Systems / Cloud · Sept. 2024 — Dec. 2024

Microservice system for retrieving and processing stock market data from external APIs with independent deployment and cloud observability.

  • Deployed six independent services to reduce coupling and support independent release cycles.
  • Used Docker, Kubernetes, and IBM Container Registry with vulnerability scanning for safer deployments.
  • Configured IBM Cloud Load Balancer and Grafana monitoring to improve reliability and issue resolution.
DockerKubernetesIBM CloudAPIsGrafana

Hangman Game

Real-Time Web Application · Jan. 2025 — May 2025

Multiplayer Hangman game with Socket.IO WebSocket updates for low-latency shared game state.

  • Implemented WebSocket game-state updates with sub-100ms latency.
  • Built robust connection handling for concurrent multiplayer sessions.
  • Reduced network overhead compared with traditional REST polling patterns.
Socket.IOWebSocketJavaScriptNode.js

Cash Canvas

Financial Desktop Application · Sept. 2023 — Dec. 2023

Qt/C++ financial application focused on efficient local data handling, SQLite query optimization, and live market data integration.

  • Optimized SQLite queries and indexing for faster retrieval on larger financial datasets.
  • Reduced memory footprint with optimized data structures and smart pointer usage.
  • Integrated REST API data streams for live market data.
C++QtSQLiteREST API

Relevant Coursework

Computer Science

Data AnalysisMachine LearningDeep LearningDiscrete MathematicsData StructuresOperating SystemsDistributed SystemsComputer System Architecture

Software Engineering

Object-Oriented ProgrammingDatabase SystemsWeb DevelopmentCybersecurity