Job Title: Cloud Platform Engineer

Location: Leeds / hybrid working

Duration: 6 months + extension (outside IR35)

Rate: £Market rates

We are seeking an experienced Cloud Platform Engineer to join a growing technology team responsible for designing, deploying, and supporting modern cloud infrastructure and container platforms. This role offers the opportunity to work across multi-cloud environments, hybrid infrastructure, Kubernetes platforms, and emerging AI technologies.

The key areas are as follows -

Azure Cloud & Hybrid Platforms

• Provisioning and management of Azure Linux Virtual Machines, managed disks, and storage services (Blob, File, and Disk storage)
• Design and administration of Azure networking, including VNets, subnets, NSGs, route tables, Load Balancers, and Application Gateways
• Implementation of secure hybrid connectivity using VPN Gateway, ExpressRoute, and site-to-site connections
• Integration of on-premises infrastructure with Azure, including identity federation (Azure AD), DNS resolution, and authentication flows
• Deployment of high availability and resilient architectures, leveraging availability sets, zones, and autoscaling
• Use of Terraform with Azure (Azurerm provider) to standardise and automate cloud provisioning

Containers & Kubernetes (AKS)

• Strong understanding of containerisation principles using Docker and Podman, including image creation, optimisation, and registry management
• Administration of Azure Kubernetes Service (AKS) clusters, including node pools, scaling, upgrades, and lifecycle management
• Deployment of containerised applications using Helm charts, YAML manifests, and CI/CD pipelines
• Configuration of persistent storage using Azure Disks, Files, and CSI drivers
• Implementation of monitoring and logging using Azure Monitor, Log Analytics, and container insights
• Troubleshooting cluster, pod, and networking issues to maintain platform reliability

Azure Red Hat OpenShift (ARO)

• Operational support and administration of Azure Red Hat OpenShift clusters, ensuring platform stability and performance
• Management of projects (namespaces), RBAC policies, and security controls
• Deployment and maintenance of Operators to extend cluster functionality
• Configuration of persistent storage and integration with Azure storage services
• Integration with Azure identity services (Azure AD) and enterprise authentication mechanisms
• Support for application teams deploying workloads into OpenShift environments

Google Cloud Platform (GCP) & Vertex AI

• Experience with Google Cloud Platform (GCP) core services, including Compute Engine, networking, IAM, and storage
• Use of Terraform (Google provider) to provision and manage GCP infrastructure in a consistent and scalable manner
• Understanding and utilisation of Vertex AI for building, deploying, and managing machine learning models
• Support for MLOps workflows, including model training, deployment, and monitoring within Vertex AI pipelines
• Integration of AI/ML services into cloud-native applications, enabling data-driven decision making
• Familiarity with GCP security and identity management, ensuring controlled access to AI and cloud resources