4 of 4 Cost Optimisation Jobs in Leeds

cloud migrations to AI enablement and platform engineering, you will lead the charge in building autonomous platforms, managing AI lifecycles, and enforcing strict cost governance across cloud estates. You are seen as a leader internally and externally, through your technical expertise, guidance, and professionalism, both … advanced Kubernetes administration (clusters, nodes, pods), hardcore networking (VPC peering, Service Mesh, Zero Trust security), and solution architecture experience, with a cost‐optimisation mindset. Software Engineering, Agentic & AI Development (30%): Solid software engineer principles (pipelines, toolsets, testing, linting, vulnerability scanning, etc.) Production‐level experience with tools such ...

Platform Automation. DevOps, CI/CD and Engineering Enablement. Security Governance and Regulatory control Cloud networking, connectivity and integration. Operational Resilience, Monitoring and Cost Optimisation. Mentoring, Standards and Engineering Culture Key Skills Required - Must have worked at a Lead level. Expert level hands-on and architectural Azure Cloud ...

GitHub Actions, Docker, Kubernetes, and cloud platforms (AWS, Azure), demonstrating success in large-scale automation delivery, including high-volume API automation and measurable cost optimisationExperience across cross-platform testing (web, mobile, API, desktop) with strong functional and automation coverage and practical experience with cloud-based and cross-browser ...

identify, communicate, and mitigate technology risks associated with distributed systems, data platform decisions, and system integrations Ensure operational excellence - design solutions with security, cost optimization, performance, regulatory requirements, and compliance in mind Contribute to architecture governance - support architecture forums and governance processes, ensuring timely review and alignment across … optimization, as well as OLTP databases such as PostgreSQL and MySQL Distributed compute frameworks – strong experience with Apache Spark and distributed data processing, including optimisation, performance tuning, and large‐scale batch/streaming workloads Cloud‐native data platforms – demonstrated experience with any Cloud Providers such as AWS, GCP, Azure ...