Senior Kubernetes Platform Engineer

You'll be using your operations skill, software crafting abilities, and teamwork to maintain and extend foundational technologies to provide highly available Kubernetes infrastructure that powers InfluxDB Cloud in 8 regions on every major cloud provider.

You'll join an awesome globally-distributed team, bringing experience in designing, implementing, and operating large-scale, multi-cloud, Kubernetes-backed infrastructure.

Your teammates work closely together to conquer projects together. They recently nurtured the adoption of SLOs throughout the engineering organization and have several proof-of-concepts running to test out theories and ideas. They’re curious, looking for the next challenge, and eager to welcome you aboard.

What you’ll do:

Operate and grow numerous Kubernetes clusters on Amazon, Google, and Azure platforms. Improve operator and developer ergonomics at scale; iterate on and directly impact and influence the InfluxDB Cloud infrastructure. Collaborate with tightly aligned teams to ensure their services are fast and resilient. Embrace the challenge of multi-cloud complexity but plan to simplify and streamline our ops practice. Mentor teammates on architecture, design, and best practices.

What you’ll need:

Experience running Kubernetes in production for at least 2 years. Strong DevOps/Ops background. We are 100% Linux,  Proficiency with Terraform, immutable infrastructure, and familiarity with the GitOps configuration management model. Hands-on, production-level experience with AWS, Google, or Azure. We use all three but do not expect you to have mastered them all.

Bonus if you've had experience: 

Operating and being responsible for Kubernetes clusters used by other engineering teams. Making data-driven observations and decisions to drive higher performance and reliability. Being an incident lead, engaging multiple groups simultaneously to resolve critical problems. Thriving in a remote-first, distributed team environment. Familiarity with CNCF technologies such as Istio, Kafka, Elasticsearch, ArgoCD, CoreDNS, etcd, Prometheus, Jaeger, and Keda Familiarity with kubeadm clusters: in other words, doing Kubernetes “the hard way”