Staff Software Engineer

Open People Network (OPN); Toronto; On-site; CAD 120,000 - 150,000; Full time

Job summary

Docnote, an early-stage Canadian health‑tech company operating in Ontario, seeks a highly autonomous engineer who can own complex problems end‑to‑end — from the initial product idea to architecture and delivery. You won't just wait for specs; you'll help create them, translate requirements into concrete design, and drive outcomes.

In this role you will shape data models, API contracts, and infrastructure decisions while collaborating with AI-enabled tooling.

Qualifications

• Ability to translate product requirements into architecture end-to-end.
• Strong systems thinking and design judgment across domains.
• Experience working with AI-enabled development and prompt-driven workflows.

Responsibilities

• Own complex problems end-to-end from product need to architecture and delivery.
• Design data models, API contracts, domain logic, and trade-offs.
• Collaborate on AI-assisted execution and evaluate outputs rigorously.

Skills

Product-Architecture Translation

Systems Thinking

AI-Augmented Execution

Tools

Java/Spring Boot

React/TypeScript

MySQL

AWS

Job description

About Docnote

Docnote is an early-stage Canadian health technology company reinventing how uninsured medical services are delivered. Physicians aren't compensated by provincial health insurance for tasks like sick notes, medical forms, disability tax credit applications, and prescription renewals - so these fall on clinics as unpaid administrative work. Docnote provides an end-to-end platform that manages the entire process, from the initial patient request through to secure payment collection and digital document delivery, integrating with existing EMR systems.

About Docnote

Docnote is an early-stage Canadian health technology company reinventing how uninsured medical services are delivered. Physicians aren't compensated by provincial health insurance for tasks like sick notes, medical forms, disability tax credit applications, and prescription renewals - so these fall on clinics as unpaid administrative work. Docnote provides an end-to-end platform that manages the entire process, from the initial patient request through to secure payment collection and digital document delivery, integrating with existing EMR systems. The company's mission is to eliminate administrative burden from the practice of medicine - giving physicians the tools to run a sustainable, modern clinic while offering patients a dignified, transparent experience. Docnote is currently operating in Ontario with an early-revenue, product-market-fit focus and a national expansion strategy.

What We're Looking For

This is a high-autonomy role for someone who can own complex problems end-to-end: understand the business need, design the solution, build it, and evolve it as the product grows. This is not a ticket-taker role. You're not waiting for specs - you're helping create them.

There are three things that matter most for this role.

1. Product-to-Architecture Translation The ability to take a product requirement - not a technical spec, a product description - and walk it all the way down on your own: UI behavior, API contracts, domain logic, data model, and infrastructure. This is the person who hears a feature description and immediately sees the full technical picture without being told what to build. It's the hardest skill to find and the one AI can't shortcut.
2. Systems Thinking and Design Judgment The ability to see how a decision ripples across the system. Not just solving the immediate problem, but understanding what it does to your domain boundaries, whether it creates coupling you'll regret, and how it affects the data model six months from now. This person makes the right trade-off between speed and structure without hand-holding. AI can generate code all day. It can't tell you whether you're building the right abstraction.
3. AI-Augmented Execution Fluency Comfort working with agentic AI as a real development partner, not just autocomplete. This means decomposing work into well-scoped, delegable units, writing specs and prompts that produce high-quality output, and reviewing AI-generated work with the same rigor you'd apply to a junior developer's PR. This skill is learnable if the first two are already there.

The Stack

• BACKEND: Java / Spring Boot
• FRONTEND: React / TypeScript
• DATABASE: MySQL
• INFRASTRUCTURE: AWS

Interview Process

1. Phone screen - 30 minutes A quick conversation to gauge fit on both sides. This is where we figure out who moves forward. The focus is on how you think and whether the product-focused framing resonates, not a technical grill.
2. Take-home design interview - async A product problem, not a coding puzzle. We hand you a feature description and ask you to walk it down into a design: data model, API contracts, domain logic, and the trade-offs you'd make and why. This is the real test of skills one and two - can you translate a product need into architecture on your own. You're welcome to use AI, since that's how we work.
3. Design discussion - 1-2 hours, live A working session on what you produced in the take-home. We walk through your design together and pressure-test it: why you made the calls you made, where it would break, and what you'd do differently at scale. This is where we confirm you understand your own work rather than just having generated it, and where skill three shows up. Anyone can produce a design. This session is where we find out if you own it.
4. Final roundtable culture fit Senior product leadership. Less about the technical work at this point and more about whether you're someone we want in the room: how you collaborate, how you handle disagreement, and whether you fit how we operate as a team.

Application Details

• First Name*
• Last Name*
• Email Address*
• Country*
• Linkedin*
• Position*
• Salary Expectation*
• Tell us about a product feature or business problem where you were given the need or desired outcome rather than a detailed technical specification. Walk us through how you took it from that initial requirement through technical design and production. What decisions did you personally make around the API, domain logic, data model, UI and/or infrastructure?*
• Tell us about an architectural decision you made where there was a meaningful trade-off between shipping quickly and designing for the longer term. What options did you consider, what did you choose, and how did that decision hold up as the product evolved?*
• Describe the most relevant production system you have personally built or substantially owned using Java and Spring Boot. What did you build, how recently were you hands-on in the code, and what experience did you have with React/TypeScript, MySQL and AWS in that environment?*
• How are you using AI or agentic development tools in your engineering work today? Give us a specific example of work you delegated or accelerated with AI, how you scoped it, and how you validated the output before it reached production?*
• Tell us about a time you worked on a small or fast-moving product team where responsibilities weren't neatly defined. How did you work with product/design or customers, decide what needs to be built, and keep delivery moving without waiting for detailed direction?*
• Tell us about a significant production issue you personally helped diagnose and resolve. What happened, what did you own, how did you approach it, and what did you change afterward?*
• Upload Resume*

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