AI Infrastructure & Operations Engineer
KYLG AB
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Benefits offered by this job
Job summary
KYLG AB in Sweden seeks an Infrastructure & Operations Engineer to design, deploy, and maintain AI server and GPU infrastructure, including NVIDIA GPU clusters, CUDA, Docker, and Kubernetes in a data center environment.
You will install, rack, cable, commission, and manage AI computing environments, deploy and optimize model training and inference workloads, and monitor system performance, power, cooling, and hardware health while supporting AI researchers and software engineers.
Qualifications
- Strong Linux system administration required.
- Experience deploying and maintaining NVIDIA GPU servers.
- Experience with data center infrastructure, including power distribution, rack installation, cabling, cooling, and hardware commissioning.
- Experience with Docker, Kubernetes, and the AI software stack.
- Experience with Python and AI frameworks (PyTorch/TensorFlow).
- Familiar with LLM deployment and enterprise networking.
Responsibilities
- Design, deploy, and maintain AI server and GPU infrastructure.
- Install, rack, cable, commission, and maintain AI servers in data center environments.
- Plan and execute AI infrastructure expansion, upgrades, and hardware lifecycle management.
- Deploy and manage Linux servers.
- Install, configure, and maintain NVIDIA CUDA, Docker, Kubernetes, and the AI software stack.
- Deploy and optimize AI model training and inference environments.
- Build and maintain AI agent platforms.
- Develop AI workflows and automation pipelines.
- Maintain AI computing clusters and GPU infrastructure.
- Monitor system performance and optimize GPU utilization.
- Monitor power distribution, cooling systems, and hardware health.
- Troubleshoot AI server hardware, GPU, networking, storage, OS and software issues.
- Support AI researchers and software engineers.
Skills
Tools
Job description
Join an expanding AI and Data Mining company as an Infrastructure & Operations Engineer, responsible for building and maintaining AI laboratory infrastructure. This role involves working with NVIDIA GPU clusters and enterprise AI platforms, focusing on deployment, operation, and optimization of AI computing environments. The position is based in a data center environment, requiring strong Linux and AI hardware experience, and offers opportunities to work with cutting-edge technologies.
- Competitive salary
- Flexible working environment
- Opportunity to work with cutting-edge AI technologies
- Career development in AI infrastructure and intelligent systems
We are an AI and Data Mining company developing. Our AI infrastructure includes NVIDIA GPU clusters, enterprise AI platforms, large-scale model training and inference environments, and intelligent AI workflow automation.
We are expanding our AI Laboratory and are looking for an experienced engineer to build and operate our AI computing environment.
- Design, deploy, and maintain AI server and GPU infrastructure
- Install, rack, cable, commission, and maintain AI servers in data center environments
- Plan and execute AI infrastructure expansion, upgrades, and hardware lifecycle management
- Deploy and manage Linux servers
- Install, configure, and maintain NVIDIA CUDA, Docker, Kubernetes, and the AI software stack
- Deploy and optimize AI model training and inference environments
- Build and maintain AI agent platforms
- Develop AI workflows and automation pipelines
- Maintain AI computing clusters and GPU infrastructure
- Monitor system performance and optimize GPU utilization
- Monitor power distribution, cooling systems, and overall hardware health
- Troubleshoot AI server hardware, GPU, networking, storage, operating system, and software issues
- Support AI researchers and software engineers
- Strong Linux system administration experience
- Experience with AI server hardware deployment, installation, maintenance, and troubleshooting
- Experience with data center infrastructure, including power distribution, rack installation, cabling, cooling, and hardware commissioning
- Experience deploying and maintaining NVIDIA GPU servers
- Experience with Docker
- Experience with Python
- Experience with CUDA
- Experience with AI frameworks (PyTorch / TensorFlow)
- Familiar with LLM deployment
- Experience with Git
- Experience with enterprise networking (10/25/100Gb Ethernet or InfiniBand)
- Experience assembling, upgrading and repairing enterprise servers
- Kubernetes
- Slurm
- Ansible
- GPU cluster management
- AI Agent Platforms
- LangChain
- MCP
- Vector Database
- RAG
- Workflow Automation
- CI/CD
- Experience with one or more:
- Multi-GPU training
- Distributed AI computing
- NVIDIA DGX
- AI Data Center
- Enterprise AI Infrastructure
- InfiniBand or other high-speed networking
- Storage systems (NAS / SAN)
- OpenAI API
- DeepSeek
- Qwen
- Llama
- Competitive salary
- Flexible working environment
- Opportunity to work with cutting-edge AI technologies
- Career development in AI infrastructure and intelligent systems
English required
Chinese is a strong advantage（Chinese (Mandarin) proficiency is highly preferred, as the role involves collaboration with our Chinese engineering teams and technical documentation.）
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