Canonical is a leading provider of open source software and operating systems to the global enterprise and technology markets. Our platform, Ubuntu, is widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include leading public cloud and silicon providers, as well as industry leaders across sectors. The company is founder-led, profitable, and growing.
This is an exciting opportunity for an exceptional software engineer passionate about open source software, Linux, and Web Services at scale. Join Canonical to build a rewarding, meaningful career working with some of the best and brightest in technology.
Our Store team develops and operates a large system of backend services powering the Snap Store and Charmhub.io marketplaces. Our services are primarily built in Python, with some Golang.
We face exciting challenges including scaling our architecture, expanding software delivery, and enhancing our offerings for IoT and enterprise solutions. If you value clean APIs, have a bias towards shipping, and believe in automated testing for reliability and speed, you'll be a great fit.
Canonical is a growing international software company working with the open-source community to deliver Ubuntu, the world's leading cloud OS. Our mission is to unlock the potential of free software for individuals and organizations. We help businesses reduce costs, improve efficiency, and enhance security with Ubuntu. With a remote-first culture, almost all teams operate remotely, setting the pace for the 21st-century digital workplace.
As a pioneer in open source, Canonical is at the forefront of cloud, AI, and IoT technology with Ubuntu at its core. We recruit globally, uphold high standards, and foster a workplace that values diversity and inclusion. Working here means thinking differently, working smarter, learning continuously, and pushing your boundaries.
We are an equal opportunity employer committed to a discrimination-free workplace, welcoming applications from all backgrounds.