Software Engineer with internship experience at Interac Corp and the Government of Ontario, building production systems that serve hundreds of thousands of users. I care about clean architecture, observable systems, and shipping things that actually work.
- 🎓 Associate's in Software Engineering – AI @ Centennial College | GPA: 4.35 / 4.5
- 🏦 Recently built cloud observability infrastructure at Interac Corp (AWS + Splunk + Terraform)
- 🏛️ Shipped features used by 276K+ ODSP clients @ Government of Ontario
Languages
Frontend
Backend & APIs
Cloud, DevOps & Tools
Databases & AI/ML
Software Engineer Intern · Interac Corp · Sep 2025 – Jan 2026
Built cloud observability infrastructure and DevOps tooling for one of Canada's core payment networks.
- Engineered ingestion pipelines routing AWS logs into Splunk, cutting mean time to detect (MTTD) incidents by 25%
- Maintained IaC using Terraform to automate provisioning and standardize AWS resources
- Supported enterprise-wide GitHub migration, enabling secure code hosting across engineering teams
Software Engineer Intern · Government of Ontario – MCCSS · Jan 2025 – May 2025
Delivered features on the MyBenefits portal, a platform serving hundreds of thousands of Ontario residents.
- Built an Angular + TypeScript feature enabling online diabetic supply requests for 276K+ ODSP clients
- Engineered a document upload module using Angular + REST APIs, increasing monthly uploads by 34%
- Published a private npm package — a custom Angular paginator — adopted across 10+ table modules
Software Engineer Intern · Government of Ontario – MAG · May 2024 – Sep 2024
Modernized internal tools for the Ministry of Attorney General used by judges and court staff.
- Built search/sort functionality and redesigned the Deputy Judges Database UI using React, C#, and SQL
- Implemented update/delete features using ASP.NET + Visual Basic, reducing data entry time by 28%
- Developed an interactive court locator using JavaScript + Google Maps API displaying 50+ locations
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React · Three.js · Node.js · MongoDB · Gemini API AI-powered web app that identifies fish species in real-time via Google's Gemini API. Features an interactive 3D aquarium built with Three.js, a global fishing map via Leaflet API, and a scalable Node/Express/MongoDB backend. |
Python · Flask · Scikit-learn · SMOTE Predictive model trained on Toronto Police's KSI dataset (18K+ records) achieving 80% fatal recall. Features a full preprocessing pipeline with SMOTE balancing, ensemble modeling, and a Flask API for real-time predictions. |
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Python · TF-IDF · Naive Bayes · Scikit-learn Binary classification model detecting spam using TF-IDF vectorization and Naive Bayes. Trained on 5,000+ samples with 3-fold cross-validation, achieving 91% accuracy. |
Currently working on new projects. Stay tuned! ⚡ |
Open to new grad SWE roles and internships — feel free to reach out!
