Platform Engineer / DevOps

• Workload: full-time
• Contract: B2B, 12 months + extensions
• Business travel: occasionally to Sweden
• 100% remote work
• The team is based in Stockholm, Sweden
• Language: fluent English (Swedish desirable)

We are looking for an experienced DevOps / Platform Engineer to take hands-on ownership of a production AI platform running large language model workloads. This is an individual contributor role with real production responsibility . While the Platform Tech Lead defines the overall technical direction, you will own platform components end-to-end and ensure that the environment remains reliable, secure and predictable in production. The platform runs on Kubernetes with Talos Linux and GPU-enabled nodes , using technologies including NVIDIA NIM and vLLM to serve LLM workloads.

Your responsibilities

• Operating and continuously improving a production-grade Kubernetes platform.

• Taking end-to-end ownership of selected platform components.

• Troubleshooting complex Kubernetes infrastructure and production issues.

• Investigating and resolving issues involving:

• unavailable nodes,

• unhealthy or hanging pods,

• Kubernetes Operators,

• CRDs and controllers,

• unexpected reconciliation behaviour,

• platform and infrastructure dependencies.

• Restoring production services and performing root cause analysis.

• Implementing improvements to prevent recurring incidents.

• Planning and performing safe rolling upgrades of Kubernetes clusters and platform components.

• Supporting highly available and predictable operation of GPU-enabled infrastructure.

• Operating infrastructure supporting LLM inference and model serving.

• Working with technologies such as NVIDIA NIM and vLLM.

• Improving automation, observability and operational processes.

• Creating reusable platform patterns and clear interfaces for product teams.

• Improving developer experience and reducing time-to-market.

• Maintaining strong security and data residency standards.

• Working closely with engineers, infrastructure teams, technical leads and business stakeholders.

We are looking for

• 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.

Nice to have

• Experience with Talos Linux.
• Experience running Kubernetes on bare metal or self-managed infrastructure.
• Experience with GPU-enabled Kubernetes environments.
• Knowledge of NVIDIA GPU Operator, NVIDIA NIM, CUDA or similar NVIDIA technologies.
• Experience with vLLM or other model-serving / inference technologies.
• Background in AI/ML infrastructure, MLOps or AI platforms.
• Swedish language skills or willingness to develop Swedish over time.