AI Engineer (Co-op)

General Magic; Toronto; On-site; CAD 25,000 - 30,000; Part time

Job summary

General Magic in Toronto seeks a co-op AI engineer to ship features on the agents and language model systems our customers rely on daily. You will work directly with our engineers on impactful AI tooling.

You will build agent workflows, prompts, and tools, write evaluative tests to prove improvements, and help debug production AI systems while collaborating across backend services and APIs. This is an onsite role in Toronto five days a week.

Qualifications

• Enrolment in a co-op program, ideally in computer science, engineering or a related field.
• Projects you've built and shipped with LLMs or agents, whether at work, school or on your own.
• Solid programming fundamentals, ideally in Python.
• Curiosity about how LLMs work, beyond calling an API.
• A bias toward shipping and learning fast.

Responsibilities

• Build and improve agent workflows, prompts and tools
• Write evals that measure whether a change actually made things better
• Help debug and fix issues in production AI systems
• Work across our backend and APIs to get features shipped

Skills

Python

LLMs/Agents projects

Shipping mindset

Education

Co-op program enrolment in CS/engineering

Job description

Who we are

For decades, insurance software has been built around rigid forms, portals and call centers that create friction for customers and drag for teams. Even as AI has advanced, most insurance work is still manual, slow and spread across disconnected systems.

General Magic builds AI agents that handle quoting, follow-ups, document collection, verification, claims intake and broker communication, connected directly to carrier, MGA and broker systems. We've raised $7.2M USD from Radical Ventures, a16z and several AI luminaries. We work onsite in Toronto five days a week.

The role

This is a co-op role on our AI team. You won't get a side project: you'll ship features on the agents and LLM systems our customers use every day, working directly with our engineers.

In this role, you will

• Build and improve agent workflows, prompts and tools

• Write evals that measure whether a change actually made things better

• Help debug and fix issues in production AI systems

• Work across our backend and APIs to get features shipped

For this role, you should have

• Enrolment in a co-op program, ideally in computer science, engineering or a related field

• Projects you've built and shipped with LLMs or agents, whether at work, school or on your own

• Solid programming fundamentals, ideally in Python

• Curiosity about how LLMs work, beyond calling an API

• A bias toward shipping and learning fast