Senior Full Stack Engineer

Flywheel Digital•Toronto, ON

8h•CA$140,000 - CA$160,000•Hybrid

About The Position

In this role, you will support our Perpetua product, which focuses on the seller and SMB market segment within the Flywheel portfolio. Perpetua provides growth optimization and reporting technology for the world’s smartest eCommerce businesses. Through the platform, brands and sellers create goals based on strategy and rely on Perpetua’s best-in-class, always-on optimization to execute tactically. Amazon Ads is a $40B business today and every retailer on the planet is replicating the Amazon playbook, we’ve already transformed the way businesses approach e-commerce and online advertising and we’re ready to continue growing. As a Senior Software Engineer - Full Stack with Perpetua, you will contribute to our core platform built primarily with Python, Django, React, TypeScript, BigQuery, and GCP. You will help build scalable systems and intuitive user experiences that power advertising optimization and analytics for thousands of eCommerce brands across Amazon, Walmart, Instacart, and emerging retail media platforms. We are looking for engineers who embrace modern AI-assisted software development practices and can leverage tools such as Claude Code, and other AI coding assistants to accelerate development while maintaining high engineering standards.

Requirements

5+ years of professional software engineering experience building and operating production systems.
Strong experience with Python and modern backend frameworks, preferably Django.
Strong experience building modern web applications with React and TypeScript.
Experience building scalable cloud applications on GCP.
Strong understanding of distributed systems, microservices architecture, and event-driven systems.
Experience working with large-scale data platforms and analytics systems, including BigQuery or similar data warehouses.
Proficiency with relational databases (PostgreSQL, MySQL, Cloud SQL) and data modeling.
Experience designing and consuming RESTful APIs and asynchronous processing systems.
Practical experience using AI-powered software development tools such as Claude Code, Cursor, GitHub Copilot, Windsurf, or equivalent.
Ability to effectively leverage LLMs for software design, coding, testing, debugging, documentation, and developer productivity.
Strong understanding of software engineering fundamentals, including algorithms, data structures, OOP, testing, design patterns, and frontend application architecture.
Experience with CI/CD pipelines, automated testing, and modern DevOps practices.
Excellent written and verbal communication skills.
Comfortable working in a highly collaborative, distributed, and agile environment.

Nice To Haves

Deep experience with React, TypeScript, modern frontend tooling, and UI performance optimization.
Experience with data engineering, ETL pipelines, and large-scale analytics workloads.
Experience with machine learning systems, LLM integrations, or AI-powered products.
Experience mentoring engineers and leading technical initiatives.
Contributions to open-source projects or strong technical community involvement.

Responsibilities

Build and maintain backend services and APIs using Python and Django, as well as customer-facing applications using React and TypeScript.
Design and implement scalable data pipelines that process terabytes of advertising and commerce data.
Develop features across the full stack, from data ingestion and processing to intuitive user interfaces and customer-facing functionality.
Design, build, and optimize data models and analytics workflows using BigQuery and cloud-native technologies.
Contribute to architecture decisions for distributed systems and modern web applications running on Google Cloud Platform (GCP).
Collaborate closely with Product, Design, Data Science, and Engineering teams to deliver customer value.
Use AI-assisted development tools such as Claude Code, Cursor, and GitHub Copilot to improve productivity, code quality, and engineering velocity.
Participate in technical design discussions, RFCs, code reviews, and mentoring of other engineers.
Continuously improve system reliability, scalability, observability, security, and frontend performance.
Help establish engineering best practices around AI-assisted software development.