Senior Software Engineer- HCP Platform Engineering

About the Job

Red Hat is seeking a Senior Software Engineer to join the HCP Platform Engineering team, building and operating ROSA (Red Hat Open Shift Service on AWS) Hosted Control Planes (HCP). ROSA HCP is Red Hat’s managed Kubernetes platform on AWS, built on a multi‑tenant architecture where Red Hat operates shared control plane infrastructure while customers run workloads in their own AWS accounts.

This is not a standard engineering role. You will write and ship production‑grade code, contribute to upstream open source projects and take ownership of production systems through on‑call. All three are equally important.

You’ll work at the intersection of software engineering and production reliability on one of Red Hat’s most complex and high‑scale platforms. The system spans multiple upstream open source projects and shared, multi‑tenant infrastructure, requiring strong engineering judgment and end‑to‑end ownership.

The team is small, highly autonomous, and trusted to solve meaningful problems—from design through production.

Red Hat’s commitment to open source extends beyond our products into how we work. We foster a growth mindset and encourage engineers to thoughtfully and responsibly use AI to reduce toil, simplify workflows, and increase impact—allowing teams to focus on solving our customers’ hardest problems.

• Contribute production‑grade software to upstream open source projects including Hyper Shift and Open Shift, owning features end‑to‑end from design and implementation through deployment and long‑term lifecycle in production
• Bring a product and systems lens to architecture decisions, ensuring designs account for scalability, operability, and real‑world production constraints from the start
• Operate as a full‑stack systems owner, participating in on‑call rotations and taking end‑to‑end responsibility for diagnosing, fixing, and preventing production issues
• Drive improvements that eliminate entire classes of failures by turning operational learning into durable product and platform enhancements
• Design and evolve observability (metrics, logs, traces) and SLOs as part of the software lifecycle, ensuring systems are measurable, debuggable, and resilient by design
• Raise the technical bar across the team through design docs, code review, pairing, and knowledge transfer during complex engineering work and incidents
• Work in a high‑autonomy engineering team where you identify the most impactful problems and lead them from concept through implementation and production adoption
• Partner as a peer with product and platform engineering teams to influence architecture, challenge assumptions, and ensure systems are built for scale, reliability, and long‑term operability
• Integrate AI‑assisted development tools (Git Hub Copilot, Cursor, Claude Code) into daily workflows for design, implementation, and debugging — using human judgment to maintain high engineering standards while increasing delivery velocity and system quality

• 8+ years of software engineering experience building and shipping production systems in cloud environments, including microservices, platforms, or distributed systems
• Strong proficiency in Go — you write production‑quality code, review it critically, and ramp quickly on large, unfamiliar codebases
• Deep, hands‑on Kubernetes experience from a builder's perspective: you've written operators, controllers, and CRDs in real‑world, multi‑tenant environments — not just operated clusters others built
• Solid understanding of AWS fundamentals (EC2, IAM, networking) and how Kubernetes platforms behave and scale on AWS
• Proven experience owning production systems under real SLOs, including participating in on‑call and leading incident response with a focus on root cause and long‑term fixes
• You ramp fast on complex, unfamiliar systems — forming a mental model and making meaningful contributions within weeks
• Highly self‑directed builder mindset: you identify high‑impact problems, propose solutions, and drive them end‑to‑end without waiting for direction
• Strong systems thinking — you naturally connect design decisions to their downstream impact on scalability, reliability, and…