Staff Kubernetes Platform Engineer, Infrastructure (GroqMetal)
Summary
Hands-on Senior Staff engineer on Groq's GroqMetal team building the Kubernetes-based platform that turns large-scale physical AI compute into a reliable, customer-consumable AI infrastructure product. Day to day: writing and operating production code — APIs, controllers, operators, reconciliation loops — for Kubernetes running large-scale AI training and inference workloads.
- Design and build core Groq platform systems: APIs, controllers, operators, reconciliation loops, and infrastructure abstractions.
- Remain deeply hands-on: Write, review, test, debug, and operate substantial production code while providing Senior Staff technical leadership.
- Embrace the market: Leverage Kubernetes to build a commercial product for AI infrastructure, delivering production-grade Kubernetes services for dedicated customers running large-scale AI training and inference workloads.
- Build a system, not just deploy technology: Apply distributed-systems principles to partial failure, retries, concurrency, consistency, idempotency, availability, and recovery.
- Design for stability and robustness: Design stable platform APIs and contracts that decouple the customer experience from changes in backend infrastructure.
- Collaborate with a team of experts: Work across infrastructure, inference, networking, infosec, and other teams to turn ambiguous platform needs into production systems.
- Experienced software engineers first: Strong experience designing, implementing, testing, shipping, and maintaining production software.
- Deep Kubernetes platform engineering experience: Experience with operators/controllers, CRDs, admission control, node lifecycle, cluster services, and production-grade platform design.
- Strong distributed-systems expertise: Practical experience reasoning about CAP, consensus, leader election, eventual consistency, state reconciliation, fault domains, and recovery.
- Experience developing infrastructure software: Experience working through a robust SDLC, including design review, automated testing, CI/CD, staged rollout, rollback, observability, and incident learning.
- Experience delivering Kubernetes as a Service: Practical knowledge and experience gained from delivering Kubernetes, cloud infrastructure, or infrastructure control planes as a commercially critical or externally consumed product is highly valued, but not required.
- Hands-on experience using coding agents: Experience using tools such as Codex, Claude Code, or similar systems/harnesses in substantive engineering work is highly valued; real-world practice matters more than commercial deployment.
- Steeped in the domain: Experience at a hyperscaler or neocloud supporting AI workloads or commercializing GPU clusters, with a strong understanding of the operational and product challenges of large-scale accelerator infrastructure.
- Comfort with ambiguity: Experience with inference platforms, accelerator/GPU infrastructure, device plugins, cloud infrastructure, or customer-facing platform products.
- Purposeful Hiring: You’re not here by accident, and neither is anyone else. Every teammate is handpicked with intention because who we build with matters.
- Builders Wanted: You’re not just riding the rocket ship, you’re building it. Your work directly shapes the trajectory of our company.
- Mission-Driven Work: We’re here to make a real impact. Our mission fuels everything we do.
- Tackling Hard Problems: If easy isn’t your thing, you’re in the right place. We solve some of the most complex and exciting challenges in our space.
- Excellence Is The Standard: High performance isn’t just encouraged, it’s the baseline. And it’s contagious.