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
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
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
Mentor senior engineers in harness engineering practices
Define quality bars, test strategies, and operational readiness criteria for agent-produced features
Serve as an escalation point for complex customer issues and production incidents

10+ years of software engineering experience with strong proficiency in Go
Deep expertise in Kubernetes internals, including controller/operator patterns, API server architecture, and cluster lifecycle management
Demonstrated experience making architectural decisions for large-scale distributed systems in production
Experience with at least one major public cloud platform at depth (GCP preferred), including compute, networking, identity, and managed services
Track record of defining and enforcing architectural standards, coding conventions, or structural constraints across a multi-engineer codebase
Strong written communication skills — ability to produce precise, structured technical documentation that serves as executable context for AI agents and as durable reference for engineers
Experience or demonstrated aptitude with AI-assisted development workflows, including critical evaluation of machine-generated code and understanding of how to design systems that AI agents can work within effectively
Ability to lead and influence without direct authority, across teams and organizational boundaries

Principal Software Engineer – GCP Hosted Control Planes

Key skills