Staff Kubernetes Platform Engineer, Infrastructure (GroqMetal)
Groq
- Location
- Hybrid (San Francisco Bay Area, Illinois · New York City Area, Illinois · Dallas-Fort Worth Area, Illinois)
- Compensation
- $270k - $401k/yr
- Employment
- Full-time
- Level
- Senior Level
Posted 2 days ago
About the role
Groq is building GroqMetal, a Kubernetes-based infrastructure platform that turns large-scale physical compute into reliable, customer-consumable AI infrastructure. This Senior Staff role involves designing and building core platform systems, including APIs, controllers, and operators, to support large-scale AI training and inference workloads.
Skills
Kubernetes
Distributed systems
Software engineering
API design
Infrastructure as a service
AI infrastructure
Controllers
Operators
CRDs
CI/CD
Observability
Cloud infrastructure
GPU clusters
System architecture
Production software
Debugging
Perks
- Hybrid Work
- Long-Term Incentive Program
Full job details
Mission:
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: 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.
Location: 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.
Responsibilities & opportunities in this role:
- 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.
Ideal candidates have/are:
- 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.
Why Join Us:
- 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.
If this sounds like you, we’d love to hear from you!
Compensation:
Groq is committed to providing competitive compensation through our Total Cash philosophy, which incorporates potential bonus value directly into base pay. The total cash salary ranges for this position, which is inclusive of the potential bonus value, is dependent by level:
- Staff: $270,400 - $365,000
- Sr. Staff: $341,400 - $401,600
Individual placement within these ranges is determined by your geographic location, experience, skills, and alignment with internal compensation standards. These ranges are specific to candidates located in the United States. Compensation for international candidates will vary based on local market dynamics. Beyond cash compensation, Groq also offers a Long-Term Incentive (LTI) Program and a robust suite of employee benefits.
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