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 OpenShift 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, HyperShift 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.

Senior Software Engineer – GCP Hosted Control Planes

Key skills