Landskapsarkitekt - Lediga jobb

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

AI Laboratory Infrastructure & Operations Engineer

About Us

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.

Responsibilities

You will participate in the planning, deployment, operation, and maintenance of our AI laboratory infrastructure, including:

• 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

Requirements

Required

• 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

Preferred

• Kubernetes
• Slurm
• Ansible
• GPU cluster management
• AI Agent Platforms
• LangChain
• MCP
• Vector Database
• RAG
• Workflow Automation
• CI/CD

Nice to Have

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

We Offer

• Competitive salary
• Flexible working environment
• Opportunity to work with cutting-edge AI technologies
• Career development in AI infrastructure and intelligent systems

Language

• 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.）

St1 är ett företag som driver energiomställningen och är verksamt i Finland, Sverige, Norge och Storbritannien. St1s energiportfölj omfattar oljeprodukter, biogas, hållbart flygbränsle (SAF), förnybar diesel (HVO) och solenergi. St1 driver också flera större projekt inom energiomställning.

Platform Engineering Lead

We are looking for a Platform Engineering Lead to join St1’s Cloud & Infrastructure team. The team owns and develops critical business platforms, including cloud infrastructure, identity management, ITSM, and security tooling.

Your main focus will be cloud infrastructure and DevOps, but your impact goes beyond technology: you will drive automation, improve ways of working, and help create self-service cloud platforms that enable developers to deliver faster and with less friction.

To succeed, you think like a developer. You understand CI/CD, software delivery, and what it takes to build and run reliable systems. You lead by example, staying hands-on while supporting your team through coaching, collaboration, and knowledge sharing. You don’t need to be an AI expert today, but you should be curious about how AI is transforming platform engineering and eager to explore its possibilities.

How you’ll help drive the change

As Platform Engineering Lead, you will:

• Lead and grow the platform engineering team by setting technical direction, supporting engineers, and encouraging continuous improvement.
• Design, build, and maintain cloud infrastructure, automation pipelines, and platform tooling.
• Build scalable cloud services using infrastructure-as-code, especially Terraform.
• Own platform services throughout their lifecycle, from design and development to operations and improvement.
• Promote DevSecOps practices with security, reliability, and observability built in.
• Enable developers across cloud and hybrid environments through better tools and processes.
• Optimize cloud costs and support FinOps practices.
• Identify automation opportunities and reduce manual platform work.
• Troubleshoot issues, improve reliability, and document decisions and practices.

What you bring

We are looking for someone who combines technical depth with a passion for enabling others. You likely have:

• Experience leading by example, coaching others, and solving complex technical challenges together.
• A strong software development background combined with hands-on infrastructure experience.
• Experience building and shipping software across the full delivery lifecycle.
• Hands-on experience with cloud platforms such as GCP and/or Azure.
• Strong knowledge of cloud-native architecture, governance, networking, IAM, security, and cost management.
• Practical experience with Terraform, CI/CD, automation, and DevSecOps.
• Curiosity and hands-on interest in AI, demonstrated through experiments, tools, or personal projects.
• A pragmatic approach to problem-solving and the ability to make decisions in uncertain situations.
• Strong communication skills with both technical and non-technical stakeholders.

Who we are looking for

We are looking for someone who lives the St1 Spirit: Curious, Commercial, Committed, and Caring. You help teams raise challenges early, follow through when things get difficult, think beyond silos, and continuously improve how we work.

Why join St1?

• Lead a platform team with real influence on St1’s technology direction.
• Stay hands-on while developing a high-performing team.
• Shape how AI transforms platform engineering and operations.
• Grow your expertise in cloud architecture, AI, and platform leadership.
• Work in a trusted Nordic technology organisation built on ownership and collaboration.

How we support your journey

At St1, we value safety, wellbeing, inclusion, and trust. You’ll work in a hands-on culture where you can explore ideas, take ownership, and grow across teams and countries.

You’ll have genuine leadership responsibility for a platform team and the services it owns, supported by competitive compensation, a bonus scheme, and opportunities to develop your career.

If you’d like to explore more about our culture, visit our career site.

What to expect after you apply

We welcome applicants from all backgrounds and are committed to an inclusive recruitment process.

Interested? Send your CV and cover letter via the Barona Career site by Thursday, 14 August 2026.

For more information, contact Barona’s Recruitment Team Lead Lassi Jyrinsalo during the August calling times: Tuesday, 4 August or Thursday, 6 August 2026 between 12–14.

Contact:

Lassi Jyrinsalo

+358 40 762 8992

lassi.jyrinsalo@barona.fi (mailto:lassi.jyrinsalo@barona.fi)

Let’s challenge the ordinary.

INDTECH