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Salary: EUR 6,500 - 9,000 / annual
Cast AI is hiring a Senior Software Engineer to work on Kubernetes automation—specifically the hard optimization problems that make clusters run at half the cost without breaking production.
The role spans multiple teams tackling interconnected challenges: node placement algorithms and provisioning, deep integrations with tools like Karpenter, workload rightsizing (vertical and horizontal), live workload migration between nodes, self-scaling storage, and GPU capacity optimization across clouds and regions. All of this runs in real time, in production, with no manual YAML tuning in the loop.
The core problem is genuinely difficult: deciding which nodes to kill, which pods to move, and which storage volumes to resize involves solving several P=NP-hard optimization problems continuously and faster than any human could attempt by hand. Get it right and you unlock massive cost savings. Get it wrong once and you've taken down something live.
You'll work on a remote-first, global team of cloud experts. The company operates a fast-paced workflow where most feature projects ship in 1–4 weeks. You'll have 10% time for personal projects or self-improvement, a learning budget for conferences and courses, and an annual hackathon.
Tech stack includes Go (strongly preferred), Kubernetes internals, cloud platforms (AWS, GCP, Azure), Karpenter, GCP Pub/Sub, gRPC, REST APIs, Prometheus, Grafana, Loki, Tempo, and GitLab/GitHub CI with ArgoCD and Kargo.
**Requirements:**
- Strong software engineering fundamentals: clean abstractions, maintainable code, justified architecture choices
- Production experience with Go strongly preferred; alternatively, strong systems programming skills in a comparable language
- Understanding of Kubernetes internals, particularly autoscaling and networking
- Demonstrated ability to drive a complex project end-to-end
- Experience with AI coding agents and agentic development workflows
- Hands-on production experience with observability tooling
- CI/CD and DevOps practices experience
- Strong English skills, both verbal and written
- Startup mindset: adaptable, proactive, comfortable with ambiguity
**Nice-to-haves:**
- Deep hands-on experience with cloud platforms (AWS, GCP, Azure) including compute, networking, and storage internals
- Deep knowledge of EKS, GKE, or AKS internals
- Container runtime experience (CRI-O, runc, containerd)
- Cloud storage depth: block storage, CSI, volume management, filesystem internals
- Low-level Linux experience: process internals, packet-level networking (NAT, iptables, conntrack, eBPF, SDN), filesystems, storage
- Low-level systems programming in C or C++
- Kubernetes or cloud-native open-source contributions
