.dev
Full Stack Developer at Vention with several years of experience building AI systems and cloud infrastructure. I thrive in cross-functional teams, translating technical architecture into actionable plans for stakeholders.
Personal Projects
Used by myself, colleagues, and training partners.
AlgoPulse
→A thin-client macOS app backed by a production FastAPI service for periodic coding interview practice—secure code execution without exposing API keys.
TrainSync
→Conversational AI agent for personalized coaching and automated scheduling — turns natural language into structured workouts and syncs to your smartwatch.
Mira
→Motion-like auto-scheduling desktop app that syncs Jira tasks and GitHub PRs with Google Calendar — so you can focus on the work, not the planning.
Claude Code Best Practices
→Interactive learning platform with AI-generated flashcard lessons published three times a week — teaching developers how to get the most out of Claude Code.
Experience
- •Built the full-stack application wrapping an AI vision pipeline (NVIDIA FoundationPose + SAM3) for autonomous bin-picking, including 3D scene calibration
- •Shipped a real-time analytics dashboard end-to-end — NestJS ingestion into TimescaleDB, surfaced in React over WebSockets
- •Drove the Nx monorepo migration across 15+ applications and 12+ shared libraries with fully automated CI/CD pipelines
- •Core contributor to the Python Machine Logic SDK — the primary interface developers use to program robotic motion paths
- •Co-built a shared React component library with TDD practices and contributed to the Jest → Vitest migration across the org
- •Optimized CI/CD with parallelized test suites, mock publishing, distributed Nx agents, and GitHub Actions workflows
- •Designed and shipped REST and gRPC APIs consumed by internal teams and external integrators
- •Built the initial E2E testing framework using Playwright and Cypress, enabling confident release cycles
- •Authored architecture and data flow diagrams that remain the engineering team's primary system reference
- •Integrated automated test suites into CI via GitHub Actions — catching regressions before merge
- •Collaborated with product, design, and firmware stakeholders to define cross-team quality metrics
- •Created reusable page-object models and test utilities adopted across multiple product teams
- •Reduced flaky test rate by 80% through deterministic waits, network mocking, and isolated test environments
- •Built a GPT-powered Excel add-in in C#/.NET using the OpenAI API — demoed to enterprise clients
- •Designed automation workflows with UiPath and Power Automate, eliminating hours of manual processing
- •Pitched AI adoption roadmaps directly to client leadership, shaping their generative AI strategy
- •Developed internal tooling that streamlined consultant onboarding and reduced setup time by 40%
- •Collaborated with senior consultants to scope technical requirements for Fortune 500 client engagements
Earlier: Strategy Consulting @ KPMG, Mech. Designer @ CAE
Areas of Expertise
Software Engineering
System architecture, API design, and full-stack development across web and robotics domains.
AI & Robotics
Perception pipelines, robot control, AI-driven development workflows, and agentic systems.
Infrastructure & Data
Cloud-native architecture, containerization, CI/CD pipelines, and monorepo tooling.
Education
McGill University
BS in Mechanical Engineering, Minor in Software Engineering
3.8 GPA · Dean's List throughout · Top 5% of faculty · Graduated with Distinction
McGill Rocket Team
Propulsion Engineer & Team Lead
McGill Rocket Team
Propulsion Engineer & Team Lead
- •Led 8-person propulsion engineering team and managed $60k+ budget to deliver competition-ready hybrid propulsion system and launch rail, awarded Best Design at Spaceport America Cup 2022
- •Conducted team's transition from off-the-shelf solid engine to student-led research and development hybrid propulsion system
- •Owned end-to-end launch rail system design, fabrication, and testing to ensure safe rocket deployment at competition
Capstone Project
In-Seat Safety Compartment for Air Canada
Capstone Project
In-Seat Safety Compartment for Air Canada
- •Designed innovative in-seat safety compartment system for secure storage of oversized and delicate passenger luggage during flight
- •Conducted testing and validation against aircraft regulatory restrictions, including FAA and Transport Canada safety standards
- •Ensured full compliance with cabin safety requirements, emergency egress protocols, and structural load specifications
Certificates
Model Context Protocol
AI system integration and tool-use patterns
Artificial Intelligence with Python
ML, neural networks, NLP, and computer vision
Learning C# for Azure DevOps
Cloud development and DevOps automation