Platform Engineer (DevOps)

Quick Facts

• Full-time
• B2B contract (12 months + extensions)
• 100% remote
• Occasional business travel to Sweden

Description

We’re looking for an experienced DevOps / Platform Engineer to take hands-on ownership of a production AI platform running large language model workloads. You will ensure the production environment remains reliable, secure, and predictable, operating end-to-end platform components. The platform runs on Kubernetes with Talos Linux and GPU-enabled nodes, using technologies including NVIDIA NIM and vLLM to serve LLM workloads.

Responsibilities

• Operate and continuously improve a production-grade Kubernetes platform
• Take end-to-end ownership of selected platform components
• Troubleshoot complex Kubernetes infrastructure and production issues
• Investigate and resolve issues such as unavailable nodes, unhealthy/hanging pods, Kubernetes Operators, CRDs/controllers, unexpected reconciliation behavior, and platform/infrastructure dependencies
• Restore production services and perform root cause analysis
• Implement improvements to prevent recurring incidents
• Plan and perform safe rolling upgrades of Kubernetes clusters and platform components
• Support highly available, predictable operation of GPU-enabled infrastructure
• Operate infrastructure supporting LLM inference and model serving
• Work with NVIDIA NIM and vLLM
• Improve automation, observability, and operational processes
• Create reusable platform patterns and clear interfaces for product teams
• Improve developer experience and reduce time-to-market
• Maintain strong security and data residency standards
• Collaborate with engineers, infrastructure teams, technical leads, and stakeholders

Requirements

• Strong hands-on experience operating Kubernetes in production
• Deep practical understanding of Kubernetes infrastructure and troubleshooting
• Experience with cluster lifecycle management and production upgrades
• Strong Linux administration skills
• Experience owning production systems and resolving complex incidents
• Understanding of Kubernetes Operators, controllers, and CRDs
• Strong troubleshooting and root cause analysis capabilities
• Good understanding of observability, monitoring, and production reliability
• Ability to work independently and take technical ownership
• Fluent spoken and written English

Benefits

• 100% remote work