Kubernetes Platform Engineer for AI Infra & Production

Groq, Inc.; United States; Hybrid; USD 185,000 - 303,000; Full time

Benefits offered by this job

Long-Term Incentive (LTI)

Employee benefits

Job summary

Groq, Inc. is seeking a Kubernetes Platform Engineer to build and operate production software inside the GroqMetal platform.

Youll extend Kubernetes with APIs, controllers, and platform services for customers running large-scale AI workloads, owning features end-to-end from design to operation. You will work across infrastructure, inference, networking, and security teams in a collaborative environment, growing toward ownership of increasingly complex systems while embracing ambiguity and rapid

Qualifications

• Experience designing, implementing, testing, shipping, and maintaining production software.
• Experience building or operating Kubernetes-based systems, including controllers/operators, CRDs, cluster lifecycle, node management, scheduling, networking, or platform services.
• Experience operating software in production and debugging problems across application, Kubernetes, networking, compute, and infrastructure layers.
• Understanding of failure handling, retries, idempotency, consistency, reconciliation, availability, and recovery.
• Comfortable with code review, automated testing, CI/CD, observability, deployment, and production operations.
• Experience building Kubernetes, cloud infrastructure, or platform capabilities consumed by customers.
• Experience using coding agents such as Codex, Claude Code, or similar tools in substantive engineering work.
• Experience with hyperscalers, neoclouds, GPUs, accelerator infrastructure, or AI workloads.
• Able to independently solve well-scoped problems, ask good questions when requirements are unclear, and work with senior engineers on broader architectural decisions.

Responsibilities

• Build production Kubernetes platform capabilities: Implement APIs, controllers, operators, automation, and platform services that support the GroqMetal product by extending Kubernetes.
• Own components end to end: Take responsibility for well-defined platform capabilities from design and implementation through testing, deployment, operation, and continuous improvement.
• Operate what you build: Improve reliability, observability, performance, and operational efficiency, and participate in diagnosing and resolving production issues.
• Build a Kubernetes platform as a commercial platform: Develop capabilities used by dedicated customers running large-scale AI training and inference workloads.
• Develop distributed systems expertise: Build software that handles retries, failures, concurrency, reconciliation, and changing infrastructure state correctly.
• Improve the platform: Identify reliability, scalability, and usability problems and deliver durable solutions.
• Collaboration is a core skill: Work within a team of experts to elevate the collective efforts of our team. Collaborate with engineers across infrastructure, inference, networking, infosec, and related teams to integrate platform capabilities holistically.
• Grow your technical scope: Contribute to design discussions, engineering practices, and technical decisions while developing toward ownership of increasingly complex platform systems.

Skills

Hands-on Kubernetes experience

Production infrastructure experience

Distributed systems fundamentals

Code review & CI/CD

Platform ownership mindset

Development tools (Codex/Claude Code)

AI infrastructure interest

Ambiguity tolerance

Software engineering background

Tools

Codex

Claude Code

Job description

Groq, Inc. is seeking a Kubernetes Platform Engineer to build and operate production software inside the GroqMetal platform.

Youll extend Kubernetes with APIs, controllers, and platform services for customers running large-scale AI workloads, owning features end-to-end from design to operation. You will work across infrastructure, inference, networking, and security teams in a collaborative environment, growing toward ownership of increasingly complex systems while embracing ambiguity and rapid