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Website: magical.com
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Magical is seeking New Grad Software Engineers to join our Toronto-based team, building intelligent automation systems that power healthcare operations. This is a full-time, on-site position for engineers ready to take meaningful ownership from day one. What This Role Involves Magical develops agent-based AI that automates complex healthcare workflows—from patient scheduling and care matching to administrative processes that directly affect how quickly patients receive treatment. Our systems orchestrate real-world healthcare environments: portals, documents, browser interactions, processing queues, model inference, human oversight, and the edge cases that no test suite predicts. As a New Grad Software Engineer, you'll help build the reliable, production-grade infrastructure that makes these automations work consistently, even in messy environments where workflows depend on document integrity, portal behaviour, clinical decision trees, and operational context that changes. Key Responsibilities Design and implement backend and full-stack systems that support AI agent creation, execution, and management Build product features for workflow configuration, validation, testing, deployment, and production observability Enhance system reliability through improved state management, error handling, alerting, and monitoring dashboards Partner with product, design, engineering, and customer teams to translate healthcare operational requirements into robust, scalable automations Own project delivery from design through deployment, monitoring, and iterative improvement based on real-world performance Learn continuously from experienced engineers while demonstrating initiative and technical judgment What We're Looking For Recent graduate or graduating soon with a degree in Computer Science, Engineering, Mathematics, or related discipline Solid understanding of core software engineering principles and demonstrated commitment to deepening that foundation Track record of shipped work—whether internships, open-source contributions, personal projects, research systems, or early-stage software Comfort navigating ambiguity and making progress when the path forward isn't immediately clear Self-directed approach to problem-solving; you don't wait for permission to contribute Ability to learn and execute quickly while maintaining code quality standards Hands-on experience using AI tools in your development workflow Preference for working in-person within a high-calibre engineering team in Toronto Bonus: hands-on experience with TypeScript, Node.js, React, Python, or comparable backend and frontend stacks; familiarity with databases, APIs, async systems, or distributed workflow patterns; side projects, developer tools, or AI-powered applications; experimentation…
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