Principal Software Engineer - GCP Hosted Control Planes

Red Hat Engineering is looking for a Principal Software Engineer to join the GCP Hosted Control Planes (HCP) team. This team builds and operates a managed service that enables organizations to run OpenShift Kubernetes clusters on Google Cloud Platform using HyperShift, hosting multiple Kubernetes control planes on shared GKE infrastructure to reduce cost and operational overhead for customers. This role sits at the intersection of distributed systems architecture and a new engineering discipline. Our team practices an agent-first development methodology where AI coding agents are a primary mechanism for producing, testing, and maintaining code. Engineers on this team function as harness engineers: they design the environments, constraints, and feedback loops that enable AI agents to do reliable work. As a Principal Engineer, you will not only work within this model but lead its evolution: defining the architectural boundaries agents must respect, designing the documentation architecture that serves as the agent knowledge base, building the enforcement mechanisms (custom linters, structural tests, CI gates) that prevent entropy, and mentoring the team in effective human-agent collaboration patterns. You will lead architectural decisions for a platform spanning GKE host clusters, HyperShift control planes, GCP networking and identity, observability, and deployment automation. You'll exercise expert judgment in specifying intent for complex systems work, evaluating whether agent-produced implementations meet the bar for production managed services, and deciding when to invest in harness infrastructure versus direct implementation. What you will do Lead the design of the GCP HCP platform architecture, including multi-region scalability, multi-tenancy and isolation, automated lifecycle management, and operational resilience Design and evolve the team's harness engineering infrastructure: the system of architectural constraints, custom linters, structural tests, CI gates, and feedback loops that enable AI agents to produce reliable work at scale Define and maintain the team's documentation architecture — a structured knowledge base that serves as the source of truth for both agents and engineers, treating AGENTS.md as the table of contents with deep references into design documents, architecture decision records, and operational runbooks Decompose complex system goals into well-bounded building blocks suitable for agent-driven implementation; evaluate when agent-generated approaches are sound and when they introduce unacceptable risk Identify and address architectural drift, entropy, and emergent quality issues across a large, agent-maintained codebase — designing systematic garbage collection processes to fight decay Lead architectural discussions across the HyperShift project, Cluster API communities, GCP platform integrations, and internal Red Hat teams Establish and enforce patterns for secure, maintainable, and observable systems — defining the module boundaries, dependency hierarchies, and interface contracts that constrain the solution space for both humans and agents Mentor senior engineers in harness engineering practices: crafting effective specifications, designing structural constraints, building agent-friendly documentation, and developing critical review skills for agent output Define quality bars, test strategies, and operational readiness criteria for agent-produced features, collaborating with Product Management and technical support to ensure production standards are met Serve as an escalation point for complex customer issues and production incidents beyond front-line technical support, applying deep platform knowledge to diagnosis and resolution Participate in on-call rotations to support production managed services Maintain a visible technical leadership presence in the Kubernetes, OpenShift, and GCP communities What you will bring 10 years of software engineering experience with strong proficie ... (truncated, view full listing at source)