Software Engineer
Hey! I'm Rawsab, a Software Engineering student at the University of Waterloo. I've worked across early-stage startups and scaling products, most recently at 
Palitronica (YC W22) and 
Node App.
Currently working on 
Keystone.
Throughout my past internships, I've worked on secure backend systems, real-time data flows, and AI-integrated features. Here's a brief overview:
HubSpotIncoming Summer 2026
Palitronica Inc.Engineered a model orchestration framework for RF anomaly detection, enabling configurable training and inference at scale.
Node AppBuilt a growth optimization agent for marketing teams, combining OCR pipelines, retrieval systems, and natural language querying.
dandelionImplemented distributed coordination systems for a blockchain network, including state sync, transactions, and event delivery.
BlackBerryDeveloped internal security tooling for dependency scanning, CVE validation, and pre-release checking for enterprise products.
CypientaEngineered scalable cybersecurity data pipelines for ingestion, alert processing, and threat intelligence automation.
I've worked across a modern and versatile tech stack, using these technologies to build scalable, production-ready systems and personal projects:
Rawsab has made an exceptional contribution to the development of our ML framework during his co-op term. He consistently demonstrated a high level of organization and ownership in approaching tasks, carefully processing requirements and delivering thoughtful, high-quality implementations. Beyond execution, he proactively introduced new ideas and played a key role in identifying and resolving multiple issues, improving both stability and usability of our systems. He was also highly effective in code reviews, providing clear, constructive feedback that improved the team's overall quality. His ability to go beyond assigned tasks, contribute strategically, and deliver impactful results clearly distinguishes his performance as outstanding. Throughout his co-op term, he consistently demonstrated exceptional technical ability, strong ownership, and a proactive mindset. He quickly understood complex requirements within our ML infrastructure and translated them into well-structured, scalable solutions. His contributions went beyond assigned tasks; he actively identified gaps, proposed improvements, and followed through with high-quality implementations. I strongly recommend him for any future roles in MLOps or software engineering. He has demonstrated the ability to work effectively in complex, production-level environments and consistently deliver impactful results. With continued experience, he has strong potential to grow into a highly capable engineer and technical leader.
