Jaden Moore

Software Engineering·McMaster University

GRADUATING_APRIL_2027

Backend and data engineer building internal tools that remove operational work.

Previously at RBC Capital Markets and TFI International, where I cut investigation time 92% and automated 18+ hours of weekly work.

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Work Experience

Reverse chronological

01/02

RBC Capital Markets

Software Developer Intern — Quantitative Technology Services

May 2026 — August 2026

Stack

Python
React
Flask
PostgreSQL
REST APIs

Cut position-break investigation time 92%, from 120 to 10 minutes, with a Python tool spanning an 8M-line server log, Oracle data, and reconciliation files.
Built a React and Flask support platform for 6+ trading and risk applications, with PostgreSQL and enterprise LDAP/NTLM authentication for 10 daily users.
Automated 10+ hours of weekly reporting through a Python ETL pipeline and REST APIs, producing reports used across 2 teams and presented to 100+ stakeholders.
Built an internal LLM analytics assistant for incident and vulnerability analysis, saving 3 hours each week.

02/02

TFI International

Software Engineer Intern

April 2025 — April 2026

Stack

Python
Azure AI
MongoDB
REST APIs

Automated load bidding with Python bots, saving operations coordinators 10 hours weekly and an estimated $25,000 annually.
Built an OCR ETL pipeline in a 3-person team using Python, Azure AI, and NoSQL, reducing manual entry about 90% for 30+ daily users.
Designed the OCR platform's MongoDB data layer and Python persistence functions, improving query performance by more than 95%.
Integrated REST APIs from 2 core systems into an internal web app, saving more than 8 hours of manual work each week.

Projects

01/03

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PROJECT_01

PocketSpotter

AI Fitness Form Coach

Real-time computer-vision coaching for lifters who want immediate feedback on form, pacing, and completed reps.

Team of four · DeltaHacks XI hackathon · Owned pose-processing pipeline, Flask integration, and workout logging.

Technical decision: Built an angle-based state pipeline over 33 MediaPipe landmarks, then connected live feedback and CSV workout logging through Flask.
Result: 98% accuracy with sub-50ms processing latency.

Stack

Python
OpenCV
MediaPipe
Flask

Source code

Team 21, Debug and Conquer, after winning the Real-Time AI Insights use case at RBC's TechPowHer Hackathon

PROJECT_02

VIAC

Virtual Investment Assistant Copilot

AI-powered copilot that combines live meeting insights, document analysis, tailored investment proposals, and onboarding in one advisor workflow.

Team of six RBC co-op students · TechPowHer Hackathon · 1st in our use case · 3rd overall of 22 teams.

Advisor workflow: Analyzed live client conversations and documents, captured requirements, and generated tailored investment proposals.
Onboarding: Prepared account-opening information and Investment Policy Statements, with a path to trigger portfolio rebalancing once client funds arrived.
Delivery: Built the proof of concept in one week and presented it live to a panel of four RBC Vice Presidents.

Stack

Generative AI
Real-Time Insights
Document Intelligence
Workflow Automation

RBC INTERNAL · NO PUBLIC LINK

PROJECT_03

Fish Species Classifier

TensorFlow/Keras CNN that distinguishes Brook Trout from Smallmouth Bass at 95% accuracy using augmented training data and Grad-CAM explanations.

Stack

Python
TensorFlow
Keras

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Education

McMaster University

Bachelor of Engineering·Software Engineering with Co-op

Relevant coursework

Data Structures & Algorithms
Software Architecture
Operating Systems
Software Testing

Contact

Open to 2027 new-grad backend and data engineering roles. Fastest reply by email.

If your team is building reliable systems, data platforms, or internal tools, I'd be glad to talk.

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