Platform Engineer Junior
Apache KafkaConfluent CloudApache Flink SQLPowerBIBackstageNext.jsReactNode.jsAzure OpenAIPostgreSQLGCPGoogle Cloud SQLGoogle Cloud Storage (GCS)TerraformGitHub ActionsGitHubBitBucketJira
- Data Platform Engineer Intern on the Data Platforms Event-Driven Services (EDS) Team; collaborate with technical product managers to identify and deliver enhancements to the Event Exchange self-serve portal, improving developer workflows and supporting alignment with target architecture.
- Develop full-stack Backstage plugins to integrate the Event Exchange self-serve portal into the Scotia Developer Portal (SDP), enabling the EDS team as the first platform team onboarded onto the SDP; establish reusable plugin architecture and contribution patterns to accelerate future platform team migrations.
- Lead the development of Catalog 2.0, an automated event catalog tracking Kafka topics, producers, consumers, ownership, and usage analytics; redesigned Power BI reporting workflows with interactive filtering and data quality enhancements, improving executive reporting efficiency 60x by reducing reporting effort from 1 hour to 1 minute.
- Designed and developed an AI-powered real-time financial crime detection POC that won 1st Place at the 2026 Confluent Data Streaming World Tour AI Day Toronto Hackathon. Leveraged Apache Flink SQL, Confluent Cloud, Kafka, and Azure OpenAI to implement anomaly detection, LLM-based alert enrichment, and AI-driven case triage workflows. Proposed the event-driven architecture as a foundation for future bank-wide real-time streaming AI applications, driving exploration of Confluent Cloud Flink-based streaming data transformation capabilities, and presented the solution to Scotiabank CTO, EVP, SVP, and VP-level leaders across Global Banking and Markets Engineering, AI & Agentic Engineering, and AML Technology.
Team Lead
Scotiabank × IMI BIGDataAIHUB arrow_outward IMI Big Data & AI Competition 2025-2026 December 2025 – April 2026
PythonPandasNumPyscikit-learnimbalanced-learnSHAPLIMENext.jsReactJupyter NotebookAnacondaGitHub
- Team Lead of Team 33. Led the team to win 1st place with a $15,000 prize among 430 competitors across 90+ teams, including PhD, Masters, and Undergraduate students.
- Engineered an interpretable, data-intensive AI Anti-Money Laundering (AML) system with data analysis pipelines spanning 16 machine learning models across individual and small business entities, leveraging customer-level features aggregated across 7 transaction types and an all-types view on largely unlabelled financial data to detect overall and transaction-specific anomalies.
- Designed a "triangle of traceability" for explainable AML by linking engineered data features, AML patterns, and a source-compliant regulatory knowledge library (FINTRAC, FINCEN, FLSC, etc.), enabling SHAP-generated, LLM-enhanced explanations that were human-readable, distinguished fraud vs. AML, and preserved auditability and factual consistency for compliance use.
- Built a full-stack Next.js web application integrating anomaly detection model results, AML case explanations, and the AML knowledge library into a unified investigator-facing workflow platform.
Project Manager & Architect
MCPFastAPINext.jsReactPostgreSQLAWSPrometheusGrafanaDockerJiraGitHub
- Project Manager and Architect for Agentiiv's MCP Gateway, a production-grade orchestration layer enabling secure AI agent to Model Context Protocol (MCP) server communication.
- Defined system scope, architecture requirements, and delivery milestones while coordinating development using Agile Scrum and Jira. Designed and deployed a containerized AWS-hosted gateway integrating 5 MCP servers (134 tools total), including PostgreSQL, Slack, and Google Workspace via a unified MCP protocol.
- Implemented core backend infrastructure including deterministic routing, JWT SSO authentication, RBAC access control, centralized logging (PostgreSQL), and rate limiting.
- Built platform reliability and observability systems including Prometheus and Grafana monitoring, plus a React dashboard for real-time visibility into request traffic, server usage, system health, and failures; enabled multi-agent workflow execution through gateway-mediated tool access.
Software & Machine Learning Engineer
PythonFastAPIOpenRouter APINext.jsReactFlutterAWS EC2GitHub
- Developed AuditMate, an AI-powered web and mobile platform for automating building energy audits at BuildingAssets. Performed data analysis and image preprocessing, and built backend APIs using FastAPI to support audit workflows.
- Integrated OpenRouter API with Google Gemini agents for computer vision-based fixture identification, manual retrieval, and energy improvement recommendations.
- Built Next.js and Flutter frontends, and deployed on AWS EC2, enabling both professional auditors and self-serve clients through automated and guided audit experiences.
Technology Director
GenAI Genesis arrow_outward October 2025 – March 2026
Next.jsReactSupabasePostgreSQLREST APIsZodJestFigmaGitHub
- Full-stack developer and organizer of GenAI Genesis 2026, Canada's largest AI hackathon with 2000+ applicants, 800+ hackers (30% increase from 2025), 250+ projects, and 90+ judges. Built and maintained the website, as well as participant and judging platforms, which supported 10,000+ uses during the hackathon.
- Designed and implemented secure REST APIs with Zod validation, database schemas, role-based access control, and user interfaces, as well as CI/CD pipelines with GitHub Actions and Vercel for scalable deployment. Collaborated with cross-functional teams, delivering a seamless hackathon experience.
Machine Learning Project Team Lead
UTMIST arrow_outward Aug 2025 – April 2026
PyTorchTensorFlowScikit-learnPandasNumPyDockerREST APIsNext.jsReactGitHubVSCodeJupyter NotebookGoogle ColabJira
- Led the development of the SceneClarity machine learning project, a modular framework for estimating scene-level reliability in autonomous vehicle perception, and managed the project using Jira.
- Analyzed and augmented a dataset of 1M+ images, developed object detection and classification models, and analyzed detection confidence for perception reliability, while achieving 95%+ accuracy on image classification tasks.
- Delivered Dockerized REST APIs and a React web application. Presented the project at conferences and events including CUCAI 2026 and EigenAI 2025.
Data & Machine Learning Engineer
UT BIOME arrow_outward September 2025 – March 2026
scikit-learnPandasNumPySupabasePostgreSQLAirflowdbtGitHub
- Built integrated bioinformatics and machine learning pipelines for the Functional Gene Expression project, enabling simultaneous benchmarking of 15+ models and achieving 3× faster analysis.
- Analyzed multi-dataset gene expression data to identify disease biomarkers and predict autoimmune diseases, trained linear, ensemble, gradient boosting, and SVM classifiers, and applied SHAP/LIME for interpretability.
- Implemented Airflow + dbt ETL pipelines to transform and store GEOparse data in a Supabase PostgreSQL database.
Game Mod Developer
Starblast.io arrow_outward August 2021 – February 2026
JavaScriptGitGitHubVisual Studio Code
- Official contributor and modder of the starblast.io game. Developed the official "Capture the Flag" mod, which has been played over 2 million times, improving performance, balance, and engagement.
- Developed multiple mods using the Starblast.io API, implementing real-time game logic in JavaScript with WebSockets, and designing custom 3D ships using CoffeeScript for Three.js rendering.
Mentor & Programming Lead
FIRST Tech Challenge (FTC) Teams 16488 & 22101 arrow_outward September 2021 – February 2026
TensorFlowOpenCVJavaAutodesk Fusion 360OnShapeGitGitHub
- Mentored and led FTC teams 16488 and 22101. Designed and led the development of PID-based motion control and finite state machine architectures for autonomous robot operation.
- Implemented real-time object detection using TensorFlow models integrated with OpenCV for vision-based decision making. Developed high-fidelity robotic simulations directly interfaced with the FTC SDK to validate control algorithms and model complex robot behaviors.
- Won 2nd place at the Ontario Provincial Championships, as well as Innovate and Design Awards.