Shopify Software Engineer Jobs in Toronto, ON (NOW HIRING)

Location: Remote
Compensation: CAD $100,000-$115,000 / year

Frank Darling designs custom engagement rings, and our software platform makes the operational complexity of that business work at scale.

A single diamond can be available from a supplier, listed on our website, shown to a client, reserved for an appointment, priced into a ring, or routed into production—and every system needs to agree on what is true. Our goal is to keep inventory, pricing, orders, and internal workflows accurate, reliable, and easy for teams to use.

We’re looking for an engineer who enjoys working at the intersection of software, operations, and business process. You should be comfortable with ambiguity, good at translating messy real-world workflows into maintainable systems, and confident making thoughtful judgment calls when there isn’t a perfect answer. You’ll work closely with non-technical stakeholders, so strong communication and documentation matter as much as the code itself.

We value autonomy, practical engineering, clear ownership, and systems that keep working long after they ship.

As a Business Systems Engineer, you will help build and operate the systems that connect our e-commerce, inventory, sales, client care, production, and gemology workflows. You’ll work on supplier data pipelines, Shopify integrations, pricing logic, internal tools, event-driven automations, and AI-assisted workflows that support teams across the company.

Some of the systems you’ll help build and maintain include:

• Inventory pipelines importing hundreds of thousands of records from dozens of suppliers

• Shopify integrations and order orchestration

• Internal tools used across Sales, Client Care, Production, and Gemology

• Pricing engines and business rules that drive our catalog

• Event-driven workflows running on AWS

• AI-assisted automation and internal tooling

• Monitoring and operational tooling that keeps the platform healthy

• Data integrations between SaaS platforms, internal systems, and production workflows

You’ll spend as much time understanding the business as you do writing code.

This role is probably a good fit if:

• You enjoy turning conversations into software.

• You ask “why?” before you ask “how?”

• You’re comfortable with ambiguity. Business problems rarely arrive as complete requirements, and you’re excited to untangle them.

• You enjoy making thoughtful judgment calls. There usually isn’t one “correct” solution—just tradeoffs.

• You’re technology-agnostic. Whether the right answer is Python, SQL, an AWS Lambda, an automation, or changing the business process itself, your goal is solving the problem well.

• You believe documentation is part of engineering.

• You get satisfaction from building systems that quietly do their jobs for years.

We’re less interested in checking every box than finding someone who enjoys this style of engineering. We’re open to a range of experience levels, from strong mid-level engineers to senior candidates; scope and compensation will reflect experience.

• 2+ years writing production Python

• Working knowledge of JavaScript, SQL, Bash, and GraphQL

• Experience designing, consuming, or debugging REST APIs

• Familiarity with AWS Lambda and ECS

• Experience working with relational databases

• Comfortable debugging production systems

• Comfortable reading and improving an existing codebase

• Experience using Git in a collaborative development environment

• Strong written communication and documentation skills

• Comfortable working directly with non-technical stakeholders

• Experience using Claude Code, Codex, or similar AI coding agents as a core part of your development workflow

AI isn’t an optional productivity tool here. It’s part of how we build software.

You should already be using Claude Code, Codex, or similar coding agents as a core part of your development workflow—not simply as autocomplete. We expect engineers to delegate implementation, investigation, refactoring, testing, and documentation to AI agents, critically review their output, and know when to trust them and when not to.

• Docker

• AWS SQS, DynamoDB, RDS, S3, API Gateway, CloudFront, or IAM

• Shopify APIs

• ETL or large-scale data integration pipelines

• Monday.com, Make.com, Trello, Zapier, or similar workflow platforms

• Google Apps Script

• Google Sheets automation

• Monitoring, alerting, or operational tooling

• E-commerce, inventory, manufacturing, or retail operations systems

• Experience integrating LLMs into production workflows

We trust engineers to make decisions.

You’ll work directly with the people running the business, ask questions, propose alternatives, and choose solutions that balance simplicity, reliability, and long-term maintainability. We value good judgment over rigid process, thoughtful tradeoffs over cleverness, and documentation over tribal knowledge.

You’ll have a great deal of autonomy, but you won’t be working in isolation. We believe the best engineering comes from understanding the business deeply, collaborating with the people closest to the problem, and building systems that make everyone’s work easier.

• You’re shipping production code into existing systems.

• You’re fielding requests from stakeholders and helping turn them into clear next steps.

• You’re using documentation, code walkthroughs, and working sessions to build context quickly.

• You’ve diagnosed and fixed issues with support from the team.

• You’re beginning to understand how inventory, pricing, orders, and internal workflows connect across the business.

• You’re independently owning small to medium projects from discovery through deployment.

• Business stakeholders are bringing you problems, not just implementation requests.

• You’re making thoughtful technical decisions and explaining your reasoning clearly.

• You’re comfortable debugging production issues across unfamiliar parts of the platform.

• You’ve improved the reliability, clarity, or maintainability of systems you inherited.

• You’re leading larger projects that affect multiple teams or systems.

• You understand the business well enough to identify better solutions than the original request.

• You’re helping shape technical direction, not just executing known work.

• You’ve built or materially improved systems that people across the company rely on every day without thinking about them.