AI Infrastructure DevOps Engineer (Kubernetes + GPU)

Carbon3.ai; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Era4 is seeking a DevOps Engineer to design, operate and improve our Kubernetes-based AI infrastructure in London. This hands-on role focuses on cloud-native platform engineering, GPU workloads, bare-metal servers and automation to deliver a secure, scalable AI platform for ML engineers and data scientists.

You will build and operate our AI infrastructure, supporting Linux systems, Kubernetes platforms and automation initiatives.

Qualifications

• Experience with Linux servers and infrastructure environments.
• Exposure to bare-metal hardware, data centres or enterprise platforms.
• Knowledge of Kubernetes and containerised environments.
• Understanding of NVIDIA GPUs, AI infrastructure or HPC environments.
• Familiarity with Infrastructure-as-Code, automation and scripting tools.
• Experience with Ansible, Git, YAML, Python or CI/CD pipelines.
• Strong troubleshooting skills and willingness to learn new technologies.
• Ability to work across infrastructure, platform and operational environments.

Responsibilities

• Deploy and maintain bare-metal servers, Linux systems and data-centre infrastructure.
• Configure, support and troubleshoot Kubernetes clusters and workloads.
• Manage NVIDIA GPU infrastructure, monitoring performance and resource utilisation.
• Automate infrastructure and operational processes using IaC and DevOps tools.
• Support security, access management and platform governance.
• Collaborate with engineering teams, vendors and customers to resolve technical issues.
• Produce technical documentation and support infrastructure deployments.
• Participate in operational support and on-call activities.

Skills

Linux

Bare-metal

Kubernetes

NVIDIA GPUs

IaC

Automation

CI/CD

Python

Git

YAML

Troubleshooting

Scripting

Tools

Ansible

Git

YAML

CI/CD pipelines

Python

Job description

Era4 is seeking a DevOps Engineer to design, operate and improve our Kubernetes-based AI infrastructure in London. This hands-on role focuses on cloud-native platform engineering, GPU workloads, bare-metal servers and automation to deliver a secure, scalable AI platform for ML engineers and data scientists.

You will build and operate our AI infrastructure, supporting Linux systems, Kubernetes platforms and automation initiatives.