{
  "instruction": "This is a resume structure for an LLM. Parse as valid JSON.",
  "schema_version": "1.0",
  "candidate": {
    "name": "Noah Oosting",
    "title": "Software Developer & AI Systems Engineer",
    "summary": "Software developer specializing in AI orchestration, enterprise systems, and intelligent automation. I bridge the gap between traditional application engineering and modern AI workflows, with a strong foundation in full-stack web, native Android, and game logic design.",
    "skills": [
      "Power BI",
      "DAX",
      "Azure SQL",
      "Microsoft Fabric",
      "Ollama",
      "Gemini CLI",
      "TensorFlow",
      "PyTorch",
      "Transformers (BERT)",
      "NVIDIA CUDA",
      "Vector Databases (RAG)",
      "Python (AI Orchestration, Automation)",
      "FastAPI",
      "Scikit-learn",
      "Pandas",
      "Java (Enterprise Patterns, SOLID)",
      "Spring Boot",
      "Thread-safe Servlets",
      "RuneLite API",
      "TypeScript",
      "Node.js",
      "Next.js 16",
      "React 19",
      "Tailwind CSS",
      "PHP/MySQL",
      "Linux (Ubuntu/Debian)",
      "Docker",
      "Model Context Protocol (MCP)",
      "C# (Unity/Godot)",
      "Oracle PL/SQL"
    ],
    "softSkills": [
      "Agile & Scrum Methodology",
      "End-to-End Project Lifecycle",
      "Team Collaboration",
      "Technical Communication",
      "Business Intelligence",
      "Ethical AI Implementation",
      "Problem Solving",
      "Adaptability"
    ],
    "certifications": [
      {
        "name": "Brandwatch Search Specialist",
        "image": "/certs/brandwatch.png"
      },
      {
        "name": "Hootsuite Platform Certification",
        "image": "/certs/hootsuite.png"
      }
    ],
    "contact": {
      "email": "noahoos@gmail.com",
      "github": "github.com/truenosus",
      "linkedin": "linkedin.com/in/noah-oosting"
    },
    "experience": [
      {
        "role": "AI Development Student",
        "company": "Fanshawe College",
        "period": "2025 - Present",
        "description": [
          "Designed and deployed advanced deep learning architectures (CNNs, RNNs, GANs) using TensorFlow and PyTorch.",
          "Implemented state-of-the-art NLP solutions utilizing Transformer architectures (BERT, GPT-3) and spaCy for intent recognition.",
          "Analyzed and mitigated machine learning security vulnerabilities, developing robust models resilient against data poisoning and evasion attacks.",
          "Optimized model performance by leveraging NVIDIA GPU hardware acceleration systems (CUDA, TensorRT).",
          "Developed precision software solutions requiring extreme focus and multitasking; Expert at mastering complex technical systems quickly."
        ]
      },
      {
        "role": "Guild Leader, Raid Organizer & Discord Administrator",
        "company": "Digital Communities (MMORPG)",
        "period": "2022 - 2024",
        "description": [
          "Led a diverse team of players in high-pressure, strategic raid environments; developed and implemented group strategies to achieve objectives.",
          "Organized weekly raids and social activities across various time zones to ensure high engagement.",
          "Recruited and mentored new members, assessing strengths and team dynamics.",
          "Analyzed player performance metrics using in-game tools to identify areas for improvement and provide feedback."
        ]
      },
      {
        "role": "Budtender Keyholder",
        "company": "True North Cannabis Co.",
        "period": "2021 - 2024",
        "description": [
          "Daily counting of till and vault; ensured 100% compliance with AGCO and Smoke-Free Ontario regulations.",
          "Educated customers on safe use, terpene profiles, and THC/CBD ratios to provide consultative sales experiences.",
          "Managed stock work, labeled shelves, and handled rigorous ID/credential verification for all guests."
        ]
      }
    ],
    "education": [
      {
        "institution": "Fanshawe College",
        "program": "Artificial Intelligence and Machine Learning",
        "period": "2025 - 2026",
        "credentials": "Post-Graduate Certificate (AIM)",
        "courses": [
          {
            "title": "Machine Learning Optimization Strategies",
            "code": "INFO-6154",
            "technologies": [
              "NVIDIA CUDA",
              "TensorRT",
              "Optuna",
              "PyTorch Profiler"
            ],
            "projects": [
              {
                "name": "Model Compression",
                "description": "Pruning and quantizing VGG16 models to reduce size by 50% while maintaining 95% accuracy for edge deployment."
              },
              {
                "name": "GPU Benchmarking",
                "description": "Profiling deep CNN training loops to identify bottlenecks and demonstrating 10x speedups via CUDA acceleration."
              }
            ]
          },
          {
            "title": "Deep Learning with Tensorflow & Keras 2",
            "code": "INFO-6152",
            "technologies": [
              "TensorFlow 2.x",
              "Keras Functional API",
              "GANs",
              "OpenCV"
            ],
            "projects": [
              {
                "name": "Generative Adversarial Networks",
                "description": "Building DCGANs to synthesize realistic facial imagery and implementing Neural Style Transfer."
              },
              {
                "name": "Sentiment Classification",
                "description": "Designing LSTM/GRU recurrent networks for high-accuracy sentiment analysis on the IMDb dataset."
              }
            ]
          },
          {
            "title": "Natural Language Processing 2",
            "code": "INFO-6153",
            "technologies": [
              "Hugging Face",
              "BERT",
              "GPT-2",
              "PyTorch"
            ],
            "projects": [
              {
                "name": "BERT Fine-Tuning",
                "description": "Adapting pre-trained BERT models for specialized financial sentiment analysis tasks."
              },
              {
                "name": "Creative Text Generation",
                "description": "Implementing autoregressive generation pipelines using GPT-2 for creative fiction."
              }
            ]
          },
          {
            "title": "Machine Learning Security",
            "code": "INFO-6149",
            "technologies": [
              "Adversarial Robustness Toolbox",
              "CleverHans",
              "Python"
            ],
            "projects": [
              {
                "name": "Adversarial Defense",
                "description": "Generating FGSM adversarial examples to fool classifiers and implementing defensive distillation to restore robustness."
              },
              {
                "name": "Data Poisoning Detection",
                "description": "Simulating training set contamination and building outlier detection systems to sanitize data."
              }
            ]
          },
          {
            "title": "Social Media Analytics",
            "code": "INFO-6155",
            "technologies": [
              "Twitter API",
              "NetworkX",
              "NLTK"
            ],
            "projects": [
              {
                "name": "Brand Sentiment Monitor",
                "description": "Real-time ingestion and sentiment classification of live social streams for brand reputation tracking."
              }
            ]
          },
          {
            "title": "Deep Learning with Pytorch",
            "code": "INFO-6147",
            "technologies": [
              "PyTorch Lightning",
              "Torchvision",
              "Transfer Learning"
            ],
            "projects": [
              {
                "name": "Custom Image Classifier",
                "description": "Training CNNs on custom collected datasets using Transfer Learning (ResNet) and data augmentation."
              }
            ]
          }
        ]
      },
      {
        "institution": "Algonquin College",
        "program": "Computer Programming",
        "period": "2020 - 2022",
        "credentials": "Ontario College Diploma",
        "courses": [
          {
            "title": "Enterprise Application Programming",
            "code": "CST8277",
            "technologies": [
              "Java EE",
              "Spring Boot",
              "JPA/Hibernate",
              "REST APIs"
            ],
            "projects": [
              {
                "name": "Enterprise REST API Service",
                "description": "Built a scalable backend service using Spring Boot, designing RESTful endpoints and implementing role-based security protocols."
              }
            ]
          },
          {
            "title": "OOP with Design Patterns",
            "code": "CST8288",
            "technologies": [
              "Java",
              "Design Patterns",
              "SOLID",
              "JUnit"
            ],
            "projects": [
              {
                "name": "Legacy Code Refactoring",
                "description": "Refactored monolithic Java applications by applying Singleton, Factory, and Strategy patterns to improve maintainability."
              }
            ]
          },
          {
            "title": "Advanced Database Topics",
            "code": "CST8276",
            "technologies": [
              "Oracle PL/SQL",
              "Stored Procedures",
              "MongoDB",
              "Data Warehousing"
            ],
            "projects": [
              {
                "name": "Hybrid Database Solution",
                "description": "Developed complex PL/SQL stored procedures for business logic automation and integrated NoSQL data streams."
              }
            ]
          },
          {
            "title": "Mobile Graphical Interface Programming",
            "code": "CST2335",
            "technologies": [
              "Android SDK",
              "Kotlin",
              "SQLite",
              "Fragments"
            ],
            "projects": [
              {
                "name": "Native Android Productivity App",
                "description": "Implemented complex UI layouts, local data persistence, and asynchronous network operations."
              }
            ]
          }
        ]
      }
    ],
    "projects": [
      {
        "name": "OpenClaw Autonomous Discord Bot",
        "description": "An autonomous agent running within the OpenClaw framework to manage and engage with Discord communities.",
        "technologies": [
          "Python",
          "OpenClaw",
          "Gemini API",
          "Discord API"
        ],
        "highlights": [
          "Implemented truly autonomous behavior that maintains context across long-running conversations while adhering to API rate limits."
        ]
      },
      {
        "name": "Custom MCP Servers & CLI",
        "description": "Developed custom MCP servers to extend the capabilities of AI assistants, allowing for direct system integration and specialized tool access.",
        "technologies": [
          "TypeScript",
          "Node.js",
          "Gemini CLI",
          "Model Context Protocol (MCP)"
        ]
      },
      {
        "name": "YouTube Channel Growth & Content Strategy",
        "description": "Creator, Editor, and Strategic Consultant focusing on organic growth strategies, SEO optimization, and audience retention metrics.",
        "technologies": [
          "Hootsuite",
          "Video Editing",
          "SEO",
          "Analytics"
        ],
        "highlights": [
          "Maintained a disciplined, long-term content schedule across multiple platforms.",
          "Orchestrated organic growth strategies for personal and partner channels."
        ]
      },
      {
        "name": "EchoLogistica",
        "description": "An atmospheric, high-fidelity 'Physical Horror' simulation built from the ground up in Godot 4.3. Focuses on tactile, diegetic interaction with 1980s-era audio equipment and complex signal processing logic.",
        "technologies": [
          "Godot 4.3",
          "GDScript",
          "GLSL Shaders",
          "Verlet Integration",
          "SQLite"
        ],
        "image": "/images/projects/echologistica.png",
        "highlights": [
          "Built a modular 'Spine' of singletons and a HardwareChassis base class for clean, decoupled event propagation.",
          "Developed a custom, deterministic kinematic interaction system for tactile physics-based object manipulation.",
          "Created physics-based patch cables using Verlet integration for real-time signal routing between machines.",
          "Utilized custom GitHub Action workflows for automated PR triage and architectural review."
        ]
      },
      {
        "name": "Daltos Draft Dashboard",
        "description": "A high-speed interactive NFL draft board built for live-streamed commentary. Features an 'auto-looks' system for automated avatar matching and a reactive rank-swapping algorithm.",
        "technologies": [
          "React 19",
          "TypeScript",
          "Vite",
          "Tailwind CSS 4",
          "Dexie.js"
        ],
        "image": "/images/projects/daltos-draft.png",
        "highlights": [
          "Built a transactional rank-swapping logic within IndexedDB to ensure data integrity and immediate UI reactivity.",
          "Developed an 'auto-looks' system for automated player avatar matching during live drafts.",
          "Utilized a zero-server architecture with Dexie.js for low-latency data persistence."
        ]
      },
      {
        "name": "Persona-Adaptive Web Engine",
        "description": "A prototype beauty salon website that dynamically re-skins its visual identity based on customer persona modeling and demographic data.",
        "technologies": [
          "JavaScript",
          "DALL-E API",
          "JSON Persona Modeling",
          "CSS Variables"
        ],
        "image": "/images/projects/persona-engine.png",
        "highlights": [
          "Developed a system that parses customer stories to determine aesthetic preferences and inject dynamic themes.",
          "Created a generative asset pipeline that automatically swaps hero banners and color palettes in real-time.",
          "Utilized AI-driven personalization to automate aesthetic selection beyond static A/B testing."
        ]
      },
      {
        "name": "Portfolio V3 (Job Site)",
        "description": "A personal portfolio and resume website built with the latest Next.js App Router and experimental UI modes. Features a modern UI using the Vercel Geist font and includes distinct 'modes' (AI, Game, Human) for viewing resume content.",
        "technologies": [
          "Next.js 16",
          "React 19",
          "TypeScript",
          "Tailwind CSS",
          "Framer Motion"
        ],
        "image": "/images/projects/portfolio-v3.png",
        "highlights": [
          "Built a multi-mode UI (Human, AI, Game) to showcase versatility in design and engineering.",
          "Utilized Next.js 16 App Router and Server Components for optimal performance and SEO.",
          "Implemented kinetic UI elements and 'fidget' mechanics using Framer Motion for enhanced user engagement."
        ]
      },
      {
        "name": "omni-job-searcher",
        "description": "A unified intelligence-gathering engine aggregating job market data via neural, semantic, and keyword search. Integrates multiple search providers (Tavily, Brave, Exa) and uses AI to extract and normalize job details into professional reports.",
        "technologies": [
          "Python",
          "Streamlit",
          "Typer",
          "Exa Neural Search",
          "Tavily AI",
          "Firecrawl API"
        ],
        "image": "/images/projects/omni-searcher.png",
        "highlights": [
          "Built a multi-provider search aggregator that normalizes disparate JSON payloads into a unified schema.",
          "Developed a 'Neural Search' workflow using Exa's auto-prompting models to bypass traditional keyword limitations.",
          "Implemented a high-performance CLI using the Rich library, featuring real-time Markdown rendering."
        ]
      },
      {
        "name": "GovCan Scraper Pipeline",
        "description": "A sophisticated data pipeline for scraping and processing Canadian government documents for RAG systems. Scrapes CRA and Service Canada documents, extracts text from PDFs, and generates vector embeddings.",
        "technologies": [
          "Python",
          "Selenium",
          "PDFPlumber",
          "OpenAI API",
          "Sentence Transformers"
        ],
        "image": "/images/projects/govcan-scraper.png",
        "highlights": [
          "Developed a robust scraping bot to autonomously harvest tax forms and guides from CRA and Service Canada.",
          "Built a PDF extraction pipeline to convert complex government forms into machine-readable JSONL.",
          "Generated vector embeddings using OpenAI and local transformers to power the AdultingOS RAG system."
        ]
      },
      {
        "name": "AdultingOS V2",
        "description": "A 'Government Document Assistant' designed to simplify complex Canadian forms. Features a wizard-style interface, plain language translations, and AI-driven form assistance to help users navigate bureaucracy.",
        "technologies": [
          "FastAPI",
          "Django",
          "React (Vite)",
          "PostgreSQL",
          "Docker"
        ],
        "image": "/images/projects/adultingos.png",
        "highlights": [
          "Designed a wizard-style form navigation system with plain language translations for accessibility.",
          "Implemented a document upload pipeline with OCR capabilities for real-time validation.",
          "Developed a scalable microservices architecture via Docker, decoupling the AI backend from the user-facing application."
        ]
      },
      {
        "name": "ML Visual Dashboard",
        "description": "An interactive data visualization tool for real-time dataset analysis and model evaluation. Allows users to upload CSV datasets, filter data, create dynamic charts, and evaluate machine learning models on the fly.",
        "technologies": [
          "Python",
          "Streamlit",
          "Pandas",
          "Plotly",
          "Scikit-learn"
        ],
        "image": "/images/projects/ml-dashboard.png",
        "highlights": [
          "Developed a Streamlit application enabling real-time CSV filtering and interactive charting.",
          "Implemented dynamic model evaluation allowing users to test `.pkl` models against custom datasets.",
          "Created automated reporting features to export predictions and visualization metrics."
        ]
      },
      {
        "name": "Adversarial ML Security",
        "description": "A research framework for investigating adversarial machine learning. Includes modules for implementing data poisoning attacks and developing defense mechanisms to protect Deep Neural Networks.",
        "technologies": [
          "Python",
          "TensorFlow",
          "Keras",
          "Scikit-learn",
          "NumPy"
        ],
        "image": "/images/projects/ml-security.png",
        "highlights": [
          "Developed a robust adversarial testing pipeline to simulate Data Poisoning attacks on CNN models.",
          "Implemented defensive strategies (input sanitization, robust training) that restored accuracy by 15% in compromised scenarios.",
          "Conducted end-to-end performance analysis generating confusion matrices to visualize robustness trade-offs."
        ]
      },
      {
        "name": "goblin-archivist-dev",
        "description": "A Godot-based prototype game demonstrating real-time LLM integration and agentic gameplay via a custom TCP middleware bridge. Relays commands between an external MCP client and the game environment.",
        "technologies": [
          "Godot 4",
          "GDScript",
          "Python",
          "TCP Sockets",
          "Threading"
        ],
        "image": "/images/projects/goblin-archivist.png",
        "highlights": [
          "Built a custom TCP socket server in Python to proxy I/O streams between LLMs and the Godot runtime.",
          "Solved isolated runtime challenges by implementing a threaded socket listener for real-time state serialization.",
          "Enabled 'Agentic Gameplay' where AI models perceive game state via JSON and execute logic in-engine."
        ]
      },
      {
        "name": "Agile Capstone Client Project",
        "description": "Lead Developer for an external client project delivering a custom software solution within a strict Agile environment. Managed the full SDLC from requirements gathering to deployment.",
        "technologies": [
          "Java",
          "Spring Boot",
          "Agile/Scrum",
          "Git Flow",
          "CI/CD"
        ],
        "image": "/images/projects/agile-capstone.png",
        "highlights": [
          "Managed the full SDLC from requirements gathering to deployment, conducting bi-weekly sprint reviews with stakeholders.",
          "Built the backend solution using Spring Boot and enforced code quality through peer reviews and CI/CD pipelines.",
          "Delivered a production-ready application that met all client acceptance criteria."
        ]
      },
      {
        "name": "RuneLite Plugin Suite",
        "description": "A collection of performance and audio enhancement plugins for the Old School RuneScape client. Includes the 'Pokemon Low HP' plugin which plays anxiety-inducing audio cues when health drops below a threshold.",
        "technologies": [
          "Java",
          "RuneLite API",
          "Maven",
          "Open Source"
        ],
        "image": "/images/projects/runelite.png",
        "highlights": [
          "Developed a real-time game state monitor hooking into the RuneLite event bus with zero latency.",
          "Created 'PokemonLowHPSoundPlugin' to dynamically overlay audio cues based on health metrics.",
          "Developed client-side rendering injections to customize game object animations."
        ]
      },
      {
        "name": "FluidWatchFace",
        "description": "A modern, declarative Wear OS watch face built entirely with Jetpack Compose for Wear.",
        "technologies": [
          "Kotlin",
          "Jetpack Compose for Wear",
          "AndroidX",
          "Gradle"
        ],
        "image": "/images/projects/watchface.png",
        "highlights": [
          "Developed a highly performant watch face using the modern Jetpack Compose toolkit, replacing legacy XML layouts.",
          "Optimized battery consumption by utilizing Compose's efficient recomposition engine.",
          "Implemented modular UI components using the compose-material library for visual consistency."
        ]
      },
      {
        "name": "NASA Image Searcher (Android)",
        "description": "Native Android app interfacing with NASA's Earth imagery API for geolocation-based satellite photography.",
        "technologies": [
          "Java",
          "Android SDK",
          "REST APIs",
          "SQLite"
        ],
        "image": "/images/projects/nasa-app.png",
        "highlights": [
          "Developed a functional mobile app consuming third-party RESTful APIs to retrieve dynamic satellite imagery.",
          "Implemented persistent local storage for managing 'Favourite' locations across sessions.",
          "Designed a user-friendly interface with strict input validation for coordinate data."
        ]
      }
    ]
  }
}