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Staff Software Engineer - Managed Kubernetes

Define and build the enterprise-grade, multi-tenant GPU orchestration platform on Kubernetes
Seattle
Expert
$314,000 – 465,000 USD / year
yesterday
Lambda

Lambda

Provides cloud GPUs and infrastructure optimized for training and deploying large-scale machine learning and AI models.

Staff Engineer

Lambda is building the AI Cloud of the future. We are seeking a Staff Engineer to help our development of our Managed Kubernetes platform. This is a foundational technical leadership role where you will shape the infrastructure that powers the next generation of AI training and inference at scale.

As a Staff Engineer on our Orchestration team, you will collaborate to help drive the technical vision for Lambda's managed orchestration services, including Managed Kubernetes, Managed Slurm on Kubernetes, and higher-level platform services for inference and AIOps. You'll work at the intersection of distributed systems, GPU-accelerated computing, and Cloud Native infrastructure to build systems that are reliable, performant, and elegantly simple for our customers.

This is not a role for someone who just operates Kubernetes; it is a technical leadership role for an engineer who has synthesized the core domains of infrastructure (compute, network, storage, security) and can design holistic solutions across all of them. You'll be working closely with NVIDIA's open-source ecosystem, and partnering with internal teams across the stack to deliver a world-class managed platform.

You are a creative, innovative engineer who operates at high velocity. You don't just solve problems. You find elegant solutions and ship them quickly. You embrace modern tools and AI-assisted development (like Claude Code) to accelerate your productivity and multiply your impact. You're energized by building new things, not maintaining the status quo.

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Staff Software Engineer - Managed Kubernetes
Seattle
$314,000 – 465,000 USD / year
Software
About Lambda
Provides cloud GPUs and infrastructure optimized for training and deploying large-scale machine learning and AI models.