{
  "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json",
  "basics": {
    "name": "Qijin Xu",
    "label": "Lead AI/ML Architect",
    "email": "qxjack@gmail.com",
    "url": "https://my-website-freedomjack.vercel.app/",
    "summary": "Lead AI/ML Architect and Tech Lead at CGI’s AI Center of Excellence with 5+ years delivering LLM agents, RAG platforms, and ML systems to enterprise production for major banks and insurers. Two-time CGI Impact Award winner spanning agent architecture, evaluation, technical leadership, and multi-cloud AI delivery. Built an LLM-powered RAG assistant that resolved about 90% of questions on its own for 50,000+ users and returned 525% ROI within 12 months. Now leading a LangGraph agent for a proprietary programming language, projected to cut manual work by 50%.",
    "location": {
      "city": "Toronto",
      "region": "ON",
      "countryCode": "CA"
    },
    "profiles": [
      {
        "network": "GitHub",
        "username": "Freedom-Jack",
        "url": "https://github.com/Freedom-Jack"
      },
      {
        "network": "LinkedIn",
        "username": "qijin-x-4899671a9",
        "url": "https://www.linkedin.com/in/qijin-x-4899671a9/"
      }
    ]
  },
  "work": [
    {
      "name": "CGI Inc.",
      "location": "Toronto, ON",
      "url": "https://www.cgi.com/",
      "position": "Lead AI/ML Architect & Tech Lead, AI Center of Excellence",
      "startDate": "2025-01",
      "highlights": [
        "CGI Impact Award 2026: led development of an LLM-powered email agent for enterprise email workflows. 89% autonomous handling across 2,000+ emails per month.",
        "Lead an AI agent for a proprietary programming language: LangGraph dual-state dynamic workflow, vLLM-served LLMs with RAG, EBNF structured outputs, and PII filtering. It writes documentation, extracts business rules, maintains legacy scripts, and prepares them for migration. Projected 50% less manual work.",
        "Architected a scalable agent evaluation pipeline with SME-adjudicated rubrics, reference cases, regression suites, and calibrated LLM-as-a-judge evaluators, for decision tasks with noisy and conflicting human labels.",
        "Drive technical direction across 13+ AI initiatives for TD Bank’s compliance SBU, guiding architecture and delivery across a cross-functional team of about 20."
      ]
    },
    {
      "name": "CGI Inc.",
      "location": "Toronto, ON",
      "url": "https://www.cgi.com/",
      "position": "Data Architect & Engineering Lead, Senior Consultant",
      "startDate": "2023-08",
      "endDate": "2024-12",
      "highlights": [
        "CGI Impact Award 2024: architected and shipped an LLM-powered enterprise RAG assistant for insurance support (LangChain; Azure, AWS, GCP). About 90% autonomous resolution for a 50,000+ user base; 525% ROI within 12 months. Product page: cgi.com/canada/en-ca/insurance-chatbot",
        "Built an OpenLineage-based lineage tool that auto-documents multi-source data flows, with LLM-assisted root-cause suggestions. Reduced investigation time across about 3 incidents per month.",
        "Automated AxiomSL rule updates at RBC with an LLM: 80% less manual updating, governance controls preserved."
      ]
    },
    {
      "name": "CGI Inc.",
      "location": "Toronto, ON",
      "url": "https://www.cgi.com/",
      "position": "Data Engineer, Consultant",
      "startDate": "2021-08",
      "endDate": "2023-07",
      "highlights": [
        "Managed Canada’s largest automobile-insurance policy-history database (2 TB, SQL Server): 99.9% uptime, median queries under 200 ms.",
        "Built production ETL/ELT pipelines for 22+ micro data marts (under 6 tables each, monthly SLAs) for finance, analytics, and delivery teams. Report runtime cut from 30 to 5 minutes.",
        "Shipped a gradient-boosting and logistic-regression loss-ratio model, batch-scored in a Python/T-SQL pipeline: 321% lift in recovered fraud losses versus a top-five bank benchmark."
      ]
    },
    {
      "name": "Elder Laboratory, York University",
      "location": "Toronto, ON",
      "position": "Research Assistant, Computer Vision (part-time)",
      "startDate": "2020-05",
      "endDate": "2021-08",
      "highlights": [
        "Worked on AttentiveVision’s computer-vision pipeline for hockey broadcast video (PyTorch, TensorFlow, OpenCV). Trained a CNN-LSTM stack reaching mAP ≥ 70% on event detection across 18 hours of game video.",
        "Built real-time player tracking with a Kalman filter and OpenPose: under 100 ms latency at 30 FPS, for live speed and heat-map analytics.",
        "Built an event-detection annotation loop (goals, timeouts, and penalties) with active learning, raising label reliability to Cohen’s kappa ≥ 0.92."
      ]
    },
    {
      "name": "Nascent Digital",
      "position": "Full-Stack Developer Intern",
      "startDate": "2019-05",
      "endDate": "2019-08",
      "highlights": [
        "Built features in React, TypeScript, and Node.js, including major parts of the company homepage rewrite, and shipped TELUS product pages with UX, QA, and DevOps, design to deploy in 7 days.",
        "Introduced visual-regression testing (Nightwatch.js, Puppeteer), removing about 90% of manual QA checks."
      ]
    }
  ],
  "education": [
    {
      "institution": "York University",
      "url": "https://www.yorku.ca/",
      "area": "Computer Science",
      "studyType": "Bachelor of Science, Specialized Honours",
      "startDate": "2017-09",
      "endDate": "2020",
      "score": "3.9/4.0"
    }
  ],
  "awards": [
    {
      "title": "CGI Impact Award",
      "date": "2024",
      "awarder": "CGI",
      "summary": "For architecting and shipping an LLM-powered enterprise RAG assistant."
    },
    {
      "title": "CGI Impact Award",
      "date": "2026",
      "awarder": "CGI",
      "summary": "For leading development of an LLM-powered email agent for enterprise email workflows."
    },
    {
      "title": "First in Class",
      "date": "2020",
      "awarder": "York University"
    },
    {
      "title": "Dean’s List (all semesters)",
      "date": "2020",
      "awarder": "York University"
    }
  ],
  "certificates": [
    {
      "name": "Microsoft Certified: Azure Solutions Architect Expert",
      "date": "2022",
      "issuer": "Microsoft"
    },
    {
      "name": "Google Cloud Professional Cloud Developer",
      "date": "2023",
      "issuer": "Google Cloud"
    }
  ],
  "publications": [
    {
      "name": "What is an AI agent?",
      "publisher": "Personal site of Qijin Xu",
      "releaseDate": "2025-04-20",
      "url": "https://my-website-freedomjack.vercel.app/writing/what-is-an-ai-agent/"
    }
  ],
  "skills": [
    {
      "name": "Languages",
      "keywords": [
        "Python",
        "Java",
        "Go",
        "SQL (T-SQL, PostgreSQL)",
        "TypeScript/JavaScript",
        "C++"
      ]
    },
    {
      "name": "AI/ML",
      "keywords": [
        "PyTorch",
        "JAX",
        "LangGraph",
        "RAG",
        "agent workflows",
        "Model Context Protocol (MCP)",
        "LLMs",
        "vLLM",
        "OpenAI API",
        "FAISS",
        "Pinecone"
      ]
    },
    {
      "name": "Data and streaming",
      "keywords": [
        "Apache Spark",
        "Kafka",
        "Airflow",
        "OpenLineage",
        "Redis"
      ]
    },
    {
      "name": "Cloud and systems",
      "keywords": [
        "Azure",
        "GCP",
        "AWS",
        "Docker",
        "Kubernetes",
        "Terraform",
        "microservices",
        "gRPC",
        "CI/CD"
      ]
    }
  ],
  "meta": {
    "canonical": "https://my-website-freedomjack.vercel.app/resume.json",
    "version": "v1.0.0",
    "lastModified": "2026-10-22"
  }
}