Software Engineer - GCP Hosted Control Planes

Red Hat Engineering is looking for Software Engineers to join the GCP Hosted Control Planes (HCP) team. This team builds and operates a managed service that enables organizations to run Open Shift Kubernetes clusters on Google Cloud Platform using Hyper Shift, hosting multiple Kubernetes control planes on shared GKE infrastructure to reduce cost and operational overhead for customers.

• Design and implement features, bug fixes, and infrastructure automation for the GCP HCP platform using Go and Kubernetes
• Work within an agent-augmented development workflow: decompose work into well‑specified tasks, guide AI agents through implementation, and rigorously review agent‑generated code and tests
• Write and maintain custom linters, structural tests, and CI gate checks that enforce architectural boundaries and prevent drift — for both human and agent contributors
• Contribute to the team's structured documentation system (design documents, architecture decision records, AGENTS.md context files) that serves as the source of truth for AI agents and humans alike
• Build and maintain the observability, deployment pipelines, and automation that support multi‑region managed Open Shift clusters on GCP
• Participate in peer code reviews with a focus on correctness, security, and adherence to established architectural constraints
• Own test strategy for the features you deliver — design test plans, write unit and integration tests, and ensure end‑to‑end coverage across the platform's multi‑region architecture
• Troubleshoot complex issues across distributed systems spanning GKE host clusters, Hyper Shift control planes, and customer workloads
• Participate in on‑call rotations to support production managed services
• Mentor peers and contribute to a culture of continuous improvement in both technical craft and agent‑augmented workflows

• 5+ years of experience developing software in a Linux environment, with strong proficiency in Go
• Experience with the Kubernetes ecosystem, including writing and operating controllers and operators
• Experience with at least one major public cloud platform (GCP preferred; AWS or Azure also relevant)
• Experience with distributed version control (Git) and CI/CD systems
• Good understanding of Linux operating systems and container runtimes
• Demonstrated ability to review code critically and troubleshoot complex issues in distributed systems
• Excellent written communication skills — you will write documentation and specifications that serve as executable context for AI agents, not just other humans
• Comfort working with AI coding tools (code generation, agent‑driven workflows, LLM‑assisted review) as part of daily development practice

• Experience with GKE, GCP networking, GCP IAM, or Workload Identity Federation
• Understanding of Hyper Shift or multi‑tenant Kubernetes control plane architectures
• Experience writing custom linters, static analysis rules, or structural/architectural tests
• Experience with infrastructure‑as‑code and Git Ops tools (Terraform, Tekton, ArgoCD)
• Experience with observability systems (Prometheus, Google Managed Prometheus)
• Participation in open source communities; contributions to Kubernetes or Open Shift upstream projects
• Experience designing or maintaining CI/CD pipelines that serve as quality gates for agent‑generated code
• Familiarity with prompt engineering, agent context design, or structured documentation practices for AI‑assisted development

The salary range for this position is $94,550.00 - $. Actual offer will be based on your qualifications.

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote‑US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience.

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