Platform Engineer (DevOps / MLOps Focus)

This Platform Engineer role focuses on DevOps and MLOps within a London-based organisation delivering an AI platform project. The position involves building and managing cloud-native infrastructure to support AI and machine learning applications, alongside designing and maintaining Kubernetes environments for production workloads. The engineer will develop and manage Infrastructure as Code using Terraform, support CI/CD pipelines and platform automation, and improve platform reliability, observability and scalability. Collaboration with Software Engineers, Data Engineers and ML teams is central to optimising deployment workflows and infrastructure performance. The salary is £100,000 per annum.

We're 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'll 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.

What you'll be doing:

• Building and managing cloud-native infrastructure to support AI and ML applications.
• Designing and maintaining Kubernetes environments for production workloads.
• Developing and managing Infrastructure as Code using Terraform.
• Supporting CI/CD pipelines and platform automation initiatives.
• Improving platform reliability, observability and scalability.
• Collaborating closely with Software Engineers, Data Engineers and ML teams to optimise deployment workflows and infrastructure performance.

Essential experience:

• 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.

Nice to have:

• Experience with Kubeflow and ML platform tooling.
• Exposure to AI, machine learning or GenAI projects.
• Experience with observability tooling such as Prometheus, Grafana or OpenTelemetry.
• Experience working within regulated or enterprise environments.

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.

49914MSR2

INDLON

The Portfolio Group are acting on behalf of our client in recruiting for this position.