Amherst, Nova Scotia, Canada
Generalist software developer with a mix of academic and industry experience in AI/Machine Learning, in addition to full-stack web and mobile application development experience across a number of software domains, including business intelligence, fintech, e-commerce, logistics, and academic research. I have experience in both startup (Oxalys Pharmaceuticals, FreightPath), enterprise (IBM, Harris Computer), scale-ups (ApplyBoard, Aurora Solar), and agency (Logikal Code) environments. I also have interests in the cognitive sciences more generally (e.g. psychology, philosophy, linguistics, neuroscience, and economics) and enjoy bringing computational tools to bear on questions in these fields. Broadly curious, data-driven decision-maker; advocate of thoughtful opinions loosely held.
Drove infrastructure improvements and testing modernization for solar design platform: Data Pipeline Stabilization – Refactored and stabilized legacy export pipeline processing 10K+ weekly solar installation designs for computer vision training datasets. Improved reliability and maintainability of Ruby/Python pipeline integrated with PostgreSQL, AWS, and Kubernetes E2E Testing Migration – Led pod transition from Cypress to Playwright. Defined critical user flows, established testing standards, and converted key test suites to improve test reliability and performance Automated Design UI – Built React interface that streamlined pre-validation and execution of automated roof designs, reducing manual effort and improving design throughput Developer Experience – Enhanced onboarding velocity through comprehensive documentation updates, local development improvements, and repository standardization Tech Stack: React, Ruby, Python, PostgreSQL, AWS, Kubernetes, Playwright, Cypress
Key Contributions: Commission Engine Integration – Designed module architecture (classes, interfaces, relationships) for an automated bulk commission rate computation system; implemented and tested core functionality Receipt-to-PDF Initiative – Led end-to-end development of an API-driven PDF generation service that aggregates multi-domain financial data and renders properly formatted documents Fintech Payment Automation – Orchestrated a three-way integration between our fintech platform, RPA team, and a corporate credit card provider to automate payment processing for school applications. Owned requirements gathering, system design, ticket breakdown, implementation, and testing strategy Tech Stack: Node.js, Nest.js, PostgreSQL, AWS, Docker, Kubernetes, GitHub Actions
Led modernization of financial systems through microservice extraction, serverless integrations, and technical debt reduction Monolith-to-Microservice Migration – Core contributor to extracting payments functionality from Ruby on Rails monolith into a Nest.js/TypeScript microservice (Postgres, Kubernetes, Docker). Designed APIs, implemented backend endpoints, and built React client pages including a complete payments history revamp NetSuite Integration – Designed and built a serverless, event-driven commission withdrawal system on AWS using CDK infrastructure-as-code. Owned database schema, Lambda logic, API Gateway configuration, and SQS queue orchestration Component Modularization – Refactored tightly-coupled financial React components into a standalone, reusable package to improve code maintainability and cross-team collaboration Technical Debt Leadership – Drove critical upgrades including TypeORM major version migration, API endpoint standardization (new resource identifier scheme), and comprehensive feature flag cleanup Microservice Enablement – Established new financial products microservice from scratch; partnered with DevOps to implement Helm charts, GitHub Actions CI/CD pipelines, and local development environments Production Operations – Served as first responder for system incidents, leveraging New Relic, AWS Redshift, and internal monitoring to diagnose and resolve issues quickly Technical Planning – Conducted spike investigations, documented findings, clarified requirements, and broke down complex initiatives into actionable, estimable tickets Tech Stack: TypeScript, Node.js, Nest.js, React, Ruby on Rails, PostgreSQL, MySQL, AWS (Lambda, CDK, SQS, Redshift), Kubernetes, Docker, Helm, GitHub Actions
As an early-stage engineer at this Invest Ottawa-backed logistics startup, I drove product development across the full stack while managing and pioneering ML initiatives: ML Product Innovation – Led development of smart freight matching and route optimization prototypes, including feasibility studies for data pipelines and ML infrastructure. Work qualified for $75K+ in SR&ED R&D tax credits Core Platform Development – Delivered full-stack features for a logistics SaaS platform serving 75+ companies, built with TypeScript, React, Nest.js, PostgreSQL, and Apollo GraphQL Data Model Redesign – Architected and implemented a business entity relationship system enabling social networking capabilities between carriers, brokers, and customers Customer Portal & Permissions – Built role-based access control system that dynamically displays shipment data based on business relationships and user permissions QuickBooks Integration – Designed and implemented OAuth 2.0-based integration module for automated invoice management and document storage DevOps & Reliability – Owned CI/CD pipeline (CircleCI, Docker, Digital Ocean, Aiven); established deployment protocols and stage-prod parity that reduced incidents by 50% in one quarter NLP Prototype – Developed few-shot learning email parser using FLAIR framework to extract structured logistics data from unstructured communications Talent Development – Participated in recruiting, interviewing, and onboarding senior engineers (retained through company acquisition) Tech Stack: TypeScript, React, Nest.js, Node.js, PostgreSQL, Redis, Apollo GraphQL, FLAIR, Docker, CircleCI, Digital Ocean
Led ML initiatives and contributed to full-stack development for utility management systems: ML Classification System – Owned end-to-end development of a supervised learning pipeline that automated classification of failed meter-reading validations. Designed experimental framework including data preprocessing, feature engineering, model training/tuning, and evaluation methodology. Achieved >90% accuracy on 50K+ samples using scikit-learn and Keras Customer Engagement Portal (MVP) – Contributed to AWS-hosted microservices prototype for cross-utility customer platform. Built RESTful payment processor and email notification service with comprehensive API documentation (Swagger) and >80% test coverage Enterprise Platform Maintenance – Delivered bug fixes and feature enhancements for legacy meter data management system (Backbone.js, jQuery, Java, Oracle/Postgres) running on Red Hat Enterprise Linux Production Support – Collaborated with customer support team to diagnose and resolve technical issues in production environments Tech Stack: Python, scikit-learn, Keras, Node.js, Express, PostgreSQL, Oracle, Java, AWS, Docker, TravisCI, Jest, Backbone.js, Swagger
-Record and report monthly and weekly meter readings for diesel generator plant. -Deliver notices of disconnection and throttled services to clients. -Provide transportation assistance to lineworkers working on downed power lines, as required. -Check and maintain power plant building fuel levels. -Maintain a clean and safe working environment.