Cloud Platform Engineer - Google Cloud (GCP)

Job Description

Salary: £60,000 - £72,000 per annum Employment type: Permanent Hours per week: 37 Reporting into: Lead Platform Engineer Department: IT Click here to read the full job description and view our excellent benefits here This role operates primarily on a remote working arrangement that will require little to no travel into our Coventry head office or various campuses. Our working model arrangements are a non-contractual benefit so please note that an Arden work location is added to our employment contracts. Sorry we cannot sponsor skilled worker visas for this role. About Arden University : We are an aspirational and multi-award-winning university, delivering rapid growth with ambitious plans to disrupt the HE sector through our passion for innovation and digital education. Our vision is to become the first-choice university for career-focused lifelong learners worldwide, ensuring that everyone, everywhere can access higher education, by leading the thoughtful integration of AI into teaching and learning and equipping our students to thrive in an AI-enabled world. There has never been a more exciting time to join Arden University , as we expand into new disciplines, forge worldwide partnerships, and expand our locations.. About our Department : The Cloud Platform Engineer - Google Cloud (GCP) sits within our Technology Department that is crucial to making sure our employees and students can work effectively, deliver projects, find the right solutions and ensure we develop the technology that will make the biggest difference. Our IT team is made up of around 100 employees with a vast range of skills from Software Development to IT Operations and Security. Our IT Department values employee development and we have lots of great examples of employee progression and promotions within the team. About the Opportunity: As a Cloud Platform Engineer - Google Cloud (GCP), you will play a key role in designing, building and operating Arden University ’s Google Cloud platform, including the cloud infrastructure and services that underpin our production Agentic AI capabilities. You will establish secure, resilient and scalable cloud foundations, develop reusable platform capabilities and strengthen DevOps practices, enabling our product, integration, data and AI teams to deliver services safely and efficiently. Combining hands-on cloud engineering with automation, infrastructure as code and platform operations, you will ensure our environments are consistent, well-governed, observable and cost-effective. Working closely with teams across Platform, Infrastructure, Cyber Security, Development, Integration, Data and AI, you will embed security, reliability and operational best practice throughout the cloud lifecycle. You will also help enable our evolving Agentic AI capabilities through secure access to models and tools, managed identities, retrieval services, runtime controls and monitoring, supporting Arden’s wider digital transformation and multi-cloud strategy. About You: Essential Skills Experience: Substantial hands-on experience engineering and operating production workloads on Google Cloud, including building and maintaining landing zones and cloud foundations. Strong knowledge of Google Cloud resource hierarchy, organisation policies, IAM, service accounts, Workload Identity, networking and secure project configuration. Practical experience with core Google Cloud services, including GKE, Cloud Run, Compute Engine, Cloud Storage, Cloud SQL, Pub/Sub, Cloud DNS, load balancing, Cloud Logging and Cloud Monitoring. Experience deploying and scaling Kubernetes and containerised services across public or private cloud environments, including GKE, EKS or AKS, alongside serverless workloads. Proficiency in Terraform, reusable modules and Infrastructure as Code, with experience implementing CI/CD pipelines using tools such as Cloud Build, GitHub Actions, GitLab CI or Azure DevOps. Strong scripting and automation skills using Bash, Python, the Google Cloud CLI and Git, with practical knowledge of Linux, networking, APIs and SQL. Experience implementing cloud security controls, including encryption, secrets management, network security, vulnerability remediation, data protection and auditable guardrails. Experience supporting production generative AI and Agentic AI services on Google Cloud, including model and agent runtimes, RAG and data grounding, tool integration, agent identities, secure access, observability and evaluation. Strong understanding of cloud monitoring and operational reliability Experience managing cloud consumption, budgets, forecasts, capacity and cost optimisation, including showback and chargeback practices. Understanding of cloud reliability, performance, scalability and capacity planning, balancing cost efficiency with operational resilience. Desirable Skills / Experience: Certifications in AWS / Microsoft Azure / Kubernetes Experience with AWS and/or Microsoft Azure in hybrid or multi-cloud en