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Distributed Systems Software Engineer - Python/Go

Distributed Systems Software Engineer - Python/Go
Canonical
remote
10 months 1 week ago

About the Role

We are seeking a software engineer with a passion for building and validating resilient distributed systems. At Canonical you can build a career and drive the success of those leveraging Canonical's Ubuntu and Juju to build multi-cloud deployable cloud applications. We see quality engineering as a first class engineering practice and are looking for people who can bring deep engineering insights and a data driven approach to test automation, reporting and data analytics.

Responsibilities

  • Create automated testing approaches and infrastructure for validating reliability, performance, and resilience of cloud orchestration tools and applications
  • Enable engineering teams across Canonical to develop software with confidence by making distributed system testing tooling available across the company
  • Enhance continuous integration pipelines for deploying and testing Canonical's cloud native products such as Kubeflow
  • Deploy, manage, and debug highly distributed systems
  • Monitor and report on automated testing efforts
  • Collaborate daily with a globally distributed team

Requirements

  • Solid background in modern test processes and strategies
  • Experience with Python or Go development
  • Strong object oriented development skills
  • Ability to develop and ship production grade modern web applications
  • Working knowledge of continuous integration tools such as Jenkins, CircleCI, GitHub CI
  • Knowledge of networking technologies and fundamentals
  • Solid understanding of Linux system architecture
  • A capacity for complex abstract thinking
  • Capability for 2-4 weeks of international travel travel per year

Additional Skills

  • Collecting and analyzing large multidimensional datasets
  • Operating data platforms: key-value stores, relational or document databases, event buses
  • Work with cloud technologies such as OpenStack, Kubernetes, Terraform and AWS
  • Developing AI/ML pipelines

Benefits

  • Distributed work environment with twice-yearly team sprints in person - we've been working remotely since 2004!
  • Personal learning and development budget of USD 2,000 per year
  • Annual compensation review
  • Recognition rewards
  • Annual holiday leave
  • Maternity and paternity leave
  • Employee Assistance Programme
  • Opportunity to travel to new locations to meet colleagues from your team and others
  • Priority Pass for travel and travel upgrades for long haul company events

Expertise level

Work arrangement

Key skills

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