Staff Kubernetes Platform Engineer, Infrastructure (GroqMetal)

Groq•Worth, IL

2d•$270,400 - $401,600•Hybrid

About The Position

GroqMetal is building the infrastructure platform that turns large-scale physical compute into a reliable, isolated, customer-consumable AI infrastructure. This is a hands-on Senior Staff role where you will write production software as part of a software engineering team. You will lead the design of a Kubernetes-based software platform focused on large-scale AI training and inference workloads. You will be a key technical leader in building the systems that turn cutting-edge physical infrastructure into a stable product. This role will be based in one of our three hiring hubs: the Dallas, San Francisco, or New York City area. The person hired for this role must be based in one of these three areas. You’ll have the flexibility to work remotely while we establish our local Groq office, with the expectation that this role will transition to onsite once the office opens.

Requirements

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.

Nice To Haves

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.

Responsibilities

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.