Live opening · Posted 4 days ago
The key details from the original listing.
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Description supplied by the original job listing.
What you get to do in this role:
You will design, build, and operate components of our Kubernetes platform and its core subsystems, owning a well-scoped area end to end.
You will write and review a lot of Go—controllers, operators, platform services, and the automation around them.
You will take a defined problem with open design questions and drive it to a working, production-ready answer, checking in on direction rather than needing it handed to you.
You will help operate what the team builds: on-call, incident investigation, and the follow-up work that stops the same failure twice.
You will contribute to how workloads run on the platform, working with the teams that depend on it.
You will work on a platform that serves regulated markets, where compliance constraints including FedRAMP shape design choices.
To be successful in this role you have:
Experience leveraging or critically thinking about how to integrate AI into engineering work — whether using AI-powered coding and operational tooling, automating workflows, or reasoning about how AI changes the way software and infrastructure are built.
Already built and shipped Kubernetes infrastructure or platform components in production. A smaller scope than a whole platform is fine, but it needs to be something you designed and owned, not something you configured or consumed.
5+ years building production software, with real experience running workloads on Kubernetes and debugging them when they misbehave.
Solid programming skills in Go, or strong systems-language skills and a clear willingness to work primarily in Go.
Working experience with at least one major hyperscaler (AWS, Azure, GCP), including its core compute, networking, and IAM primitives.
Comfort with containers, CI/CD and GitOps-based delivery, and infrastructure-as-code.
Curiosity about how AI changes platform engineering—using AI-powered tooling, automating operational work, or thinking about what it means for how infrastructure is built and run.
It also helps if you have:
Experience building Kubernetes controllers or operators with the operator pattern.
Exposure to container networking (CNI), service mesh, or workload identity and mTLS.
Experience with secrets management, certificate lifecycle, or similar core platform subsystems.
Experience with observability tooling—metrics, tracing, and SLOs.
Experience with managed Kubernetes (EKS/AKS/GKE), Terraform, or Crossplane.
Employment type
Full-time
Work arrangement
Hybrid
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