New Graduate Software Engineer, Magical
Agentic AI platform fully automating complex workflows
Job no longer available
Agentic AI platform fully automating complex workflows
21-100 employees
Job no longer available
21-100 employees
Company mission
To free the global workforce of mundane, soul-crushing workflows.
Role
Who you are
- You are graduating soon or recently graduated with a degree in Computer Science, Engineering, Math, or a related technical field
- You have strong software engineering fundamentals and are excited to keep improving them
- 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 move quickly, learn quickly, and care about shipping reliable work
- 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
Desirable
- You have experience with TypeScript, Node, React, Python, or similar backend/full-stack technologies
- You have worked with databases, APIs, queues, async systems, or distributed workflows
- You have built side projects, developer tools, automation projects, or AI-powered products
- 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
What the job involves
- As a New 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, escalate 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
Our take
It’s generally accepted that most workers in many sectors will complete at least one repetitive computer task within their work day. Magical is a platform hoping to remove the ache of these mundane tasks through its automation system.
The company doesn’t use specific integrations or APIs, rather, it simply collects repeatedly used data that can then be collated on the likes of a Google sheet or email. The platform stops you from typing the same thing over and over by populating repeatedly used text such as contact information. It's said to save an average of seven hours of work a week with its free-to-download Chrome extension.
Founded in 2020, Magical has attracted considerable funding and a growing enterprise footprint. Alongside this, the company has worked with over 10,000 businesses, including Salesforce, Uber, Bolt, Disney and Facebook, and is now moving beyond simple productivity tools into more advanced AI-driven automation. Recent partnerships, such as with Beacon Health System, signal a shift toword agentic AI capable of executing complex workflows within existing systems, particularly in high-stakes environments like healthcare.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (2 rounds)
Jun 2022
$35m
SERIES A
Sep 2020
$6m
SEED
Total funding: $41m
Company HQ
SoMa, San Francisco, CA
Leadership
Harpaul Sambhi
(Co-Founder & CEO)Previously founded Careerify (Acquired by LinkedIn) where he served as CEO. He also worked in Product Management at LinkedIn and Microsoft.
Rosie Chopra
(Co-Founder & COO)Previously spent nearly 5 years at Atlassian in various roles, including Director and then Head of Strategy & Business Operations. She also worked at Deloitte for 3 years as a Manager of Strategy & Operations.
Prashant Viswanathan
(Co-Founder)Prashant has extensive experience in Software Engineering including working as Software Engineer at LinkedIn. He then went on to become Vice President of Engineering at Swift Medical.
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