Software Developer Intern -
May, 2018 - Aug, 2018
- Implemented Machine Learning into the DevOps pipeline by developing a Slack chatbot which uses NLP to automate the containerization, monitoring, reporting, and orchestration of in-production micro-services. Saving an estimated 20 hours per microservice each week in deployment time to production.
- Created integrations for Docker, Kubernetes, Jenkins, Ansible, Vault, OpenShift, Pivotal Cloud Foundry, Microsoft Azure, Dyntrace, Kibana and Elasticsearch to ensure secure deployment, metrics reporting and horizontal pod scaling of in-production microservices, on multiple cloud platforms and VM clusters during peak load times, all from Slack.
- Created Jenkins library plugins to migrate and deploy legacy Java microservices to IBM z/OS while encapsulating build and deployment logic.
Full Stack Developer Intern -
University of Toronto
Sep, 2017 - Feb, 2018
- Developed a scalable web application using Django, Bootstrap, jQuery, Nginx, and PostgreSQL for tracking employee hours and enrollment trends for several departments.
- Created real-time updates for concurrent operation by multiple users using Django-Channels, Redis and Web-Sockets.
- Developed a REST API for calculating employee hours and for generating visualization using Chart.js for long-term trends.
QA Automation Engineer Intern -
May, 2017 - August, 2017
- Developed a web application for concurrent execution, viewing, documentation, and logging of automated scripts with real-time data analytics using Django, MongoDB, Django-Channels, Redis, Bootstrap, jQuery, Nginx, and Jenkins. Saving the department $100,000+ per year, while reducing execution time by 80%.
- Developed a web-based database viewer for MongoDB using Django and DataTables.
- Responsible for creating automated test cases via Python scripting and the Selenium library.
- Created test scripts using C# and LeanFT to automate testing of the IBM mainframe.
Back-end Developer -
May, 2016 - August, 2016
- Developed an e-commerce CRUD application using Bootstrap, Django, Nginx, and MongoDB.
- Migrated the entire back-end to cloud-based solution allowing rapid scaling.
- Containerized application using Docker to ensure rapid deployment.