We are looking for Infrastructure Engineers passionate by Performance - people with a applicational Performance mindset obsessed about performance analysis, automation, scalability and infrastructure reliability. As part of this team, you will be joining +50 other high-skilled Engineers by developing automation and tools for Cloud Orchestration, Infrastructure Automation and CI/CD Pipelines, and support other teams on the test development, performance analysis and performance mindset evangelization.
We use our own tools, built on top of state of the art technology, to build and manage an Infrastructure of +2000 cloud servers that support our production/live services and our teams of software engineers.
What you’ll do
Develop automation and tools to empower other teams on the Performance test development, execution and analysis.
Follow good practices about scale, performance, geo-distribution, multi-cloud, multi-cdn, code maintenance, documentation etc. Keep Evolving, Keep Improving.
Fully own what you build by supporting colleagues on using and extending the automation and tools so that they can deliver faster, better, harder, stronger! You did it, you own it!
Who you are
Engineer passionate about performance and building tools and automation for your fellows engineers.
Fluent in English both spoken and written.
OS/Core Systems: Linux and Windows, but you need to have an overall knowledge of all key components of an Infrastructure.
Programming: Python, Go, Java, .Net, bash, Powershell etc.
Observability: Any time series database or distributed tracing system.
APM: Any APM (commercial or not) as long you know the basic concepts, purpose and key features of an APM.
CDN: Any CDN provider as long you know the basic CDN concepts and configuration capabilities.
Performance testing tools: Good knowledge on client side and server side performance tools.
Not afraid of challenges. There are no “problems”, only a better challenge.
You are proactive, you like to help others, “Team Player” is your Middle Name.
You don’t want to learn, you need to learn.