ashby
Staff DevOps Engineer
Nexxa
Remote, USA
Full-time
Senior · 6+ years experience
Remote
Discovered 1 weeks ago
AWSGCPAzureKubernetesTerraformPulumi
Free
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Role Overview
We're looking for a Senior/Staff DevOps Engineer who has spent the last several years building and operating the infrastructure that lets AI and industrial systems run reliably at scale. You understand what it takes to keep production ML and data workloads fast, observable, and resilient — from GPU-backed training and inference clusters to the pipelines that connect them to real-world industrial environments.
This role is ideal for candidates who want deep infrastructure ownership at a company where uptime, latency, and reliability directly affect physical operations — not just software. You'll partner closely with AI, data, and product engineering teams to make sure the systems they build can actually run in production, safely and at scale.
Key Skills for This Role
AWSGCPAzureKubernetesTerraformPulumi
Full Job Posting
About the Role
We're looking for a Senior/Staff DevOps Engineer who has spent the last several years building and operating the infrastructure that lets AI and industrial systems run reliably at scale. You understand what it takes to keep production ML and data workloads fast, observable, and resilient — from GPU-backed training and inference clusters to the pipelines that connect them to real-world industrial environments.
This role is ideal for candidates who want deep infrastructure ownership at a company where uptime, latency, and reliability directly affect physical operations — not just software. You'll partner closely with AI, data, and product engineering teams to make sure the systems they build can actually run in production, safely and at scale.
What You'll Do
Own and evolve Nexxa's core infrastructure — compute, networking, storage, and deployment systems — end-to-end
Design and operate CI/CD pipelines that support fast, safe iteration across AI, data, and product engineering teams
Build and maintain infrastructure-as-code (e.g., Terraform, Pulumi) for reproducible, auditable environments across cloud and on-prem/edge deployments
Architect and manage Kubernetes-based platforms for training, inference, and application workloads, including GPU scheduling and autoscaling
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