Software Engineer · Backend, Full-Stack & AI
Matteo Pesenti
Software engineering student at the University of Waterloo. I work across the whole stack, and everything I build these days is AI-first.
About
I’m a software engineer who works across the whole stack, with a pull toward backend systems and, lately, the AI infrastructure around them: on-call agents, MCP servers, and the tooling that keeps them dependable in production.
Outside of that, I spend most of my free time mountain biking, playing poker, and shooting pool.
Experience
- Built an on-call automation agent that auto-triages pipeline failures and restores broken DAGs: it restarts jobs, opens fix PRs, and suppresses noisy alerts with human-in-the-loop escalation, cutting manual pipeline intervention by 65%.
- Built internal MCP servers and AI agents that let engineers query internal systems and debug pipeline issues in natural language.
- Built automated document parsing tools in Python to extract structured cap table data from fund documents, streamlining data ingestion for Carta's fund administration platform.
- Developed a full-stack investor referral flow using React and Python/Django, enabling fund managers to track and manage investor referrals across the Investor Experience product.
- Delivered full-stack features enabling PE and VC firms to monitor portfolio company valuations, cap tables, and investment performance metrics across Carta's platform.
- Built React + Flask customer portal editor with REST/gRPC APIs for businesses to customize WiFi portal experiences.
- Developed React component for dynamic portal advertisements using gRPC services and S3 integration.
- Built Kafka consumer for venue metadata migration, integrating Foursquare, Google Places, and Yelp APIs.
- Created Go testing framework for PostgreSQL with schema cloning and parallel CI execution.
- Engineered full-stack wildfire hazard mapping application with Flask APIs and React interface for real-time visualization.
- Analyzed geospatial data to identify correlations between greenery, temperature, and socio-economic factors across Canadian cities.
- Developed Python + Qt desktop tool for wildfire-resilient building guidelines with integrated GIS data.
- Built full-stack diagram-solving tools and notification systems with React frontends and FastAPI backends.
- Fine-tuned and deployed image classifier with diagram-solving capabilities, boosting user engagement by 8%.
- Migrated ML services from Hugging Face to Baseten, reducing latency spikes by 30%.
Contact
Have a role, a project, or just want to talk shop? Send a message below, or email me directly