Platform Engineer (DevOps / MLOps Focus)

Salary: £100,000 – 100,000 per year

Requirements:

• Strong commercial experience with Kubernetes.
• Hands‑on experience building Infrastructure as Code using Terraform.
• Experience working with cloud platforms such as AWS, Azure or GCP.
• Experience with containerisation technologies including Docker.
• Strong understanding of CI/CD principles and DevOps best practices.
• Experience supporting highly available, scalable production environments.
• Experience with Kubeflow and ML platform tooling is desirable.
• Exposure to AI, machine learning or GenAI projects is desirable.
• Experience with observability tooling such as Prometheus, Grafana or OpenTelemetry is desirable.
• Experience working within regulated or enterprise environments is desirable.

Responsibilities:

• We build and manage cloud‑native infrastructure to support AI and ML applications.
• We design and maintain Kubernetes environments for production workloads.
• We develop and manage Infrastructure as Code using Terraform.
• We support CI/CD pipelines and platform automation initiatives.
• We improve platform reliability, observability and scalability.
• We collaborate closely with Software Engineers, Data Engineers and ML teams to optimise deployment workflows and infrastructure performance.

Technologies:

• AI
• AWS
• Azure
• CI/CD
• Cloud
• DevOps
• Docker
• GCP
• Grafana
• Support
• Kubeflow
• Kubernetes
• Machine Learning
• OpenTelemetry
• Prometheus
• Terraform

More:

We are partnering with an organisation delivering a cutting‑edge AI platform project. This is an opportunity to join a highly technical team building the cloud infrastructure and platform capabilities that power large‑scale AI and machine learning solutions. You will play a key role in designing, building and maintaining scalable, secure and resilient platform infrastructure, enabling engineering and data teams to deploy and operate AI workloads efficiently. This is a fantastic opportunity to join a high‑profile AI programme with significant investment and visibility, working alongside some of the brightest engineers in the industry to build the next generation of AI infrastructure.

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