Work Experience

Red Hat

May 2020 — Aug 2021

Cloud/Software Engineer Intern

Reduced deployment time by 66% by implementing a solution for deploying locally-compiled binaries onto Kubernetes/OpenShift via command-line, cutting average deployment times from 45 minutes to 15 minutes. (Kubernetes/GoLang used for this and three below).
Eliminated 80% of manual configuration errors by enabling the Kubernetes operator to automatically fetch data from deployed services and update configurations, deprecating legacy startup scripts and reducing overall startup time by 40%.
Improved application stability by introducing startup probes for legacy applications with longer boot times, resulting in a 50% reduction in startup-related failures and downtime during production launches.
Enhanced system reliability by refactoring probes to assign default values dynamically based on deployed YAML files and fixing reconciliation issues, increasing probe accuracy by 30% and preventing misconfigurations.
Increased CI pipeline efficiency by rewriting the Jenkins (Groovy) nightly pipeline to run in a GitHub PR environment, allowing for automated testing of all team-submitted PRs prior to merging, reducing manual intervention by 60%.
Demonstrated leadership and collaboration by actively contributing to Agile sprint planning in a 12-member team, driving improvement in sprint velocity through optimized task delegation and idea generation.
Increased project reproducibility by taking initiative to write a reusable GitHub parameters file for the pipeline, enabling 100% reusability and ensuring consistent pipeline setups across different environments.
Streamlined developer onboarding by authoring comprehensive project documentation and mentoring an incoming intern, reducing onboarding time by 50% and enhancing new team members’ productivity within their first sprint.

Projects

Rarity Surf

Oct 2021

Developed a full-stack web application to generate rarity rankings for NFT's integrated with OpenSea's API, enabling users to quickly identify rare NFT's and check their listing status, improving market research efficiency by 80%.
Reverse engineered a proprietary ranking algorithm to mirror the leading rarity ranking site’s results, achieving 99.75% accuracy by utilizing data scraping techniques with Selenium, increasing the platform's trustworthiness among users.
Optimized purchasing strategy by leveraging the app to frontrun competitors in purchasing top 0.5% rarity NFTs, boosting acquisition success rate by 90% and allowing users to gain a competitive edge in the marketplace.
Architected a robust Django (Python) backend to fetch and process NFT metadata from IPFS, store rarity rankings in PostgreSQL, and serve the data via GraphQL API, ensuring low-latency access and scaling to handle 2,000+ concurrent requests.
Developed a dynamic React frontend using hooks to load rarity data in real-time, styled with Tailwind for mobile responsiveness, improving user experience and reducing frontend load times by 70%.

Skills

JavaScript, React, Python, Django, Node.js, PostgreSQL, MongoDB, Bash, Git, Linux, Command Line, Go(Lang), AWS, Kubernetes, Terraform, Docker (Compose), Jenkins, Groovy, Solidity, C

Education

University of Toronto

2019 — 2024

Computer Science Specialist — 3.84 GPA (CS). Graduated with High Distinction.

References

See my LinkedIn for references from my Red Hat managers/mentee, a startup client and a graduate student mentor.