Description
CloudLinux builds Linux infrastructure and security products. You will join our Automation & Management Services cell, working closely with Dmitrii Petrov to solve problems across teams and services: cloud-cost data, infrastructure inventory, network policies and capacity workflows.
Check out our website for more information
Inside the Infrastructure Department, the Platform cell is a small team. We run the observability platform, the company’s GitLab and the CI runners behind it, a few smaller engineering services, and the automation the department relies on for provisioning and configuration.
We are looking for a Platform Engineer for the PaaS team to take ownership of an agreed set of platform services: keep them reliable and within agreed service levels, make changes and recovery repeatable, and reduce recurring operational work through automation and self-service.
You get real freedom in how you implement things, and you own the result: you pick the approach, defend it in review, and answer for how the service behaves afterwards.
Most of the job is what site reliability engineering is about: services that run well day after day, and requests from product teams handled properly. Some of it is building. The observability platform and the runner cluster were both built from scratch within the last year, and there will be more of that. Expect the work to split between platform engineering, incident response, and helping engineers in other teams use what we run.

Run the observability platform. Keep it healthy, onboard teams, watch cost and capacity, and maintain the alerting that runs on top of it.
Run GitLab and the CI runner fleet. Upgrades, capacity, access, backups and restore drills.
Keep the rest of our services healthy, with the monitoring and runbooks a production service needs.
Deploy new services when they are requested. Research the options, pick a design, and stand the service up from scratch according to good practice: as code, monitored, backed up, documented.
Work with developers’ requests. Access, onboarding, pipeline problems, new exporters and dashboards. Answer them, and turn the recurring ones into self-service.
Run incidents. Diagnose and mitigate impact, restore service safely, then complete the root-cause analysis and post-mortem. Deliver the prevention or detection improvements the incident calls for.
Ship everything as code, reviewed in merge requests. Plan and check before every change.
Write for engineers outside the team. Runbooks, onboarding guides, maintenance notices and status updates that people can act on.
Work with AI agents. Delegate collection and drafting to them, review their output as you would a colleague’s merge request, and record what you learn where the team can find it.