Senior Software Engineer, Kubernetes Automation

New

Cast AICloud infrastructure

We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Cyprus, Malta, Finland, Sweden, Ireland, Moldova, North Macedonia, Montenegro, Slovenia, and Ukraine.Full-TimeSenior

SalaryCompetitive salary (€6,500 - €9,000 gross, depending on the level of experience)

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Job Details

Languages: Strong English skills, both verbal and written.
Required Skills: AWSGCPKubernetesAzureGoCI/CDDistributed Systems

Requirements

Have strong software engineering fundamentals, including designing clean abstractions and writing maintainable code.
Have production experience with Go, or demonstrate strong systems programming skills in a comparable language.
Understand Kubernetes internals, including autoscaling and networking.
Have personally driven a complex project end-to-end.
Have experience with AI coding agents and agentic development workflows.
Have used observability tooling in production.
Have experience with CI/CD and DevOps practices.
Have strong verbal and written English skills.
Be adaptable, proactive, and comfortable with ambiguity.
Cloud platform experience with AWS, GCP, or Azure is a nice-to-have.
Knowledge of EKS, GKE, or AKS internals is a nice-to-have.
Container runtime experience with CRI-O, runc, or containerd is a nice-to-have.
Cloud storage, block storage, CSI, volume management, or filesystem internals experience is a nice-to-have.
Low-level Linux or systems programming experience, including C or C++, is a nice-to-have.
Kubernetes or cloud-native open-source contributions are a nice-to-have.

Responsibilities

Design and build distributed systems that operate Kubernetes infrastructure autonomously at scale.
Write production Go services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management.
Own features end-to-end, from design through implementation, testing, and production rollout.
Debug complex production issues across cloud providers, Kubernetes clusters, and distributed services.
Collaborate with product and engineering teams to solve problems without textbook solutions.
Work with time-series data, cloud provider APIs, and Kubernetes control plane internals.
Contribute to product direction and backlog.
Participate in on-call rotation for teams that require it.

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