About Me
Engineering AI & Data Systems at Scale
I'm Qijin Xu, also go by Jack, an AI‑driven software engineer and data architect based in Toronto. I build production‑grade systems that fuse massive data pipelines with cutting‑edge machine‑learning models — turning raw information into real‑time intelligence and business impact.
Bio
Current Role
As a Senior Consultant at CGI, I lead enterprise AI initiatives and steward Canada's largest auto‑insurance database. Recent wins include launching a Retrieval‑Augmented‑Generation chatbot and an autonomous workflow agent that streamline claims operations company‑wide.
Expertise & Stack
Python, TypeScript, T‑SQL, Azure, Databricks, LangChain — end‑to‑end ownership from data ingestion to full‑stack ML services.
Credentials
B.Sc. in Computer Science, York University · Microsoft Certified: Azure Solutions Architect Expert · Project Management Professional (PMP).
Beyond Code
Open‑source contributor, I am a big video gamer and I love to build game assistant tools.
Skills
AI & LLM Engineering
Backend & System Design
Cloud & DevOps
Programming Languages
Data & ML Infrastructure
Full‑Stack Development
Experience
CGI
Lead Data Engineer & Software Development Engineer, Senior Consultant
- Great things are happening here.
Lead Data Engineer & Software Development Engineer, Consultant
- AI‑powered Customer‑Service Chatbot (RAG, Azure + AWS): Architected and shipped a retrieval‑augmented LLM that now resolves ~70 % of inbound queries autonomously, deflecting ≈ 8000 tickets per month and paying back its build cost 525% in 12 months.
Data Engineer, Consultant
- Database operations (SQL Server / 2 TB): Managed Canada's largest automobile-insurance policy-history database, holding 99.9 % uptime and < 200 ms median queries.
- Micro data marts (Postgres / SQL Server): Designed 22+ single-purpose marts (≤ 4 tables, monthly refresh) for accounting & finance analytics, driving monthly report runtime down from 30 min to 5 minutes.
- ML fraud scoring: Shipped a gradient-boost loss-ratio model that lifted recovered fraud losses 321 % versus a top-5 bank's benchmark, batch-scoring in a Python–T-SQL pipeline.
Elder Laboratory, York University
Research Assistant
- Automated Sports Video Analysis (PyTorch / TensorFlow): Co-developed the AttentiveVision pipeline for hockey broadcast footage, training a CNN-LSTM stack that reached mAP ≈ 70% on event detection across 18 hours of game video.
- Real-Time Player Tracking System: Engineered a smooth-pursuit Kalman-filter tracker delivering < 100 ms latency at 30 FPS, capturing sub-pixel player trajectories for live speed & heat-map analytics.
- Action Spotting & Annotation Automation: Built an active-learning annotation loop that cut manual labelling effort and raised dataset reliability to κ ≈ 0.92.
Nascent Digital
Full-Stack Developer Intern
- Homepage & Feature Revamp (React / TypeScript): Contributed major components to a company-wide homepage rewrite, working with senior devs to cut Time-to-Interactive ≈ 45%.
- Telus Product Pages: Partnered with UX, QA, and DevOps to launch two Telus product pages; reusable React components and CI hooks trimmed design-to-deploy turnaround from 10 to 3 days.
- Automated Visual Regression: Helped introduce a Puppeteer + Jest visual-diff pipeline that removed about 90% of manual QA checks and shaved 2 days off each sprint's release gate.
Education
B.Sc in Computer Science (Specialized Honours)
York University, Toronto
- Graduated with GPA: 3.9/4.0
- First Class with Distinction
Certifications
Microsoft Certified: Azure Administrator Associate
Microsoft
Issued: 2022
Project Management Professional (PMP)
Project Management Institute
Issued: 2023