Devops Engineer - Kubeops Team

Wix Wix · Enterprise · Vilnius, Lithuania · Other

Wix is seeking a DevOps Engineer to manage and evolve their large-scale Kubernetes environments. The role involves building platform components, integrating AI into operations with LLM-powered tools for investigation, planning, and coding, and owning ambiguous tasks from start to finish. Requires 3+ years of experience in infrastructure management, Kubernetes operations, cloud providers (AWS preferred), and Infrastructure-as-Code. Experience with observability tools (Prometheus, Grafana) and building internal tooling in Go or Python is also needed. Hands-on experience with AI-assisted development tools is a must.

What you'd actually do

  1. Manage the lifecycle of our large-scale Kubernetes environments, without disrupting the thousands of services running on it.
  2. Own and evolve the cluster building blocks — Kubernetes Architecture, Karpenter configurations, addons, networking, autoscaling. Where it makes sense, platformize them so other infra teams can consume them cleanly
  3. Lead the charge in integrating AI into our ecosystem—building LLM-powered tools that accelerate investigation, planning, and coding for the whole team.
  4. You’ll take ambiguous tasks and transform them into high-quality outcomes, owning every decision along the way.

Skills

Required

  • 3+ years in managing infrastructure
  • operating production systems at large scale
  • 3+ years running production Kubernetes
  • Strong understanding of core control-plane and cluster components
  • hands-on experience debugging, upgrading, and tuning autoscaling and cluster networking
  • 3+ years with a major cloud provider (AWS preferred)
  • solid grasp of core compute, networking, and IAM
  • 3+ years with Infrastructure-as-Code
  • writing and maintaining reusable modules (Terraform, Pulumi, Crossplane, etc.)
  • Observability at scale — Prometheus, Grafana, alert design
  • Building internal tooling in Go or Python
  • Hands-on experience with AI-assisted development tools and agents (Claude Code, Codex, Cursor) for knowledge gathering, debugging, coding, planning, and design
  • ability to integrate these into concrete workflows that demonstrably accelerate your work

Nice to have

  • Cluster autoscaling in production
  • Cost / capacity optimization at fleet scale — Karpenter consolidation, bin-packing, spot strategy
  • Linux internals and node-level debugging
  • Track record of leading projects end-to-end: scoping, execution and delivery

What the JD emphasized

  • hands-on experience with AI-assisted development tools and agents