Containerization & Virtualisation Engineer
Pubblicato il 06-09-2026 - Canonical in Turbigo
About Canonical
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 the world's leading public cloud and silicon providers, and industry leaders in many sectors. The company is a pioneer of global distributed collaboration, with 1000+ colleagues in 70+ countries and very few office‑based roles. Teams meet two to four times a year in person in interesting locations around the world to align on strategy and execution.
The company is founder‑led, profitable and growing.
Technology Focus
This is a general selection process for software engineers focused on virtualisation and container technology – from the kernel through userspace. Apply if you are an exceptional Go, Rust or C/C++ engineer and want to work on next‑generation open source VMM or container technology, or related open source networking and storage. Container,
virtualisation and cloud infrastructure are essential for modern software deployments. We invest in open source related to application isolation, workload orchestration, system or OCI containers, micro‑service architecture, or cloud infrastructure.
Here are some examples of projects underway at Canonical:
- RustVMM – a new hypervisor for Linux focused on performance, security and operability.
- Rockcraft – an elevated Docker image experience for the open source community.
- LXD – a modern system container and virtual machine manager used on Ubuntu, ChromeOS and other Linux platforms, covering low‑level kernel work, filesystems, VMMs, networking, and higher‑level REST API and CLI.
- Kubernetes (MicroK8s & Charmed Kubernetes) – building on‑rail K8s, Charmed Kubernetes, and operations tooling.
- OpenStack (Charmed OpenStack, OVN/OVS, Ceph) – delivering cloud platform technologies to large‑scale computing envir