Responsibilities

- As a Current Grad Software Engineer, you will help build the systems that power Magical’s AI agents
- Under the hood, Magical orchestrates long-running, high-stakes healthcare workflows involving queues, run state, browser automation, model calls, evaluations, observability, and human‑in‑the‑loop recovery
- These systems need to be reliable, debuggable, and resilient because they operate in messy real‑world environments
- A workflow might depend on a payer portal changing, a document being malformed, a model output needing review, a human needing to step in, or an edge case no one has seen before
- You will help turn messy customer inputs — SOPs, decision trees, payer rules, portal behavior, operational know‑how, and edge cases — into reliable automations
- You may work on systems that draft workflows, test automations, catch failures, recommend fixes, elevate to humans, improve runtime reliability, or make our agents easier to build and deploy
- The problems will not always be well defined
- That is part of the job
- Design and build backend and full‑stack systems for AI agents and healthcare automations
- Build product and platform features for automation creation, workflow pathways, testing, editing, monitoring, and production reporting
- Improve reliability through better run state management, queues, error classification, alerts, dashboards, and observability
- Collaborate with product, design, deployment engineering, and customer‑facing teams to turn real healthcare workflows into production‑grade automation systems




- Own projects from implementation through deployment, monitoring, iteration, and customer impact
- Learn from senior engineers while taking on meaningful responsibility early

Qualifications

- You have strong software engineering fundamentals and are excited to keep improving them.
- You move quickly, learn quickly, and care about shipping reliable work.
- You are graduating soon or recently graduated with a degree in Computer Science, Engineering, Math, or a related technical field.
- You are excited about AI and already use AI tools to improve how you code, debug, learn, or build.
- You want to work in person with a high‑caliber team in Toronto.
- You have built meaningful projects, internships, research systems, open‑source work, startups, or production software.
- You are comfortable with ambiguity and can make progress even when the answer is not obvious.
- You are a self‑starter who takes ownership instead of waiting to be handed every next step.
- You have experimented with LLMs, agents, browser automation, evaluations, or model‑powered workflows.
- You have worked in a startup, research lab, internship, hackathon team, or environment where you had to figure things out quickly.
- You have built side projects, developer tools, automation projects, or AI‑powered products.
- You have worked with databases, APIs, queues, async systems, or distributed workflows.
- You have experience with TypeScript, Node, React, Python, or similar backend/full‑stack technologies.

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📌 New Graduate Software Engineer (Toronto)
🏢 Magical
📍 Toronto