Lead, Cloud & AI Cost Optimisation

Lead, Cloud & AI Cost Optimisation

About the opportunity

An established enterprise is seeking a FinOps Lead to own the financial management and cost optimisation framework for its shared AI platform.

You will provide visibility and control across Azure cloud services, on-premises OpenShift environments, GPU infrastructure and generative AI consumption. Working closely with Engineering, Infrastructure, Finance and Procurement, you will ensure platform investments support business value, efficient utilisation and reliable performance.

Key responsibilities

• Own and maintain a centralised FinOps framework covering cloud infrastructure, container platforms, GPU resources and generative AI consumption.
• Optimise AI expenditure through model selection, routing, caching, prompt efficiency and usage controls, tracking cost per request and business use case.
• Analyse OpenShift resource utilisation and recommend right-sizing, workload scheduling and quota changes across CPU, memory, storage and GPU resources.
• Optimise Azure expenditure through right-sizing, reservation and commitment planning, storage optimisation, scheduling and removal of idle resources.
• Establish tagging, cost allocation and chargeback/showback standards to attribute expenditure accurately to projects, teams and applications.
• Own platform budgeting, forecasting, variance analysis and regular management reporting.
• Support procurement through demand forecasting, quotation evaluation, commercial analysis and contract or commitment planning.
• Develop dashboards, alerts and unit-cost metrics to monitor expenditure, utilisation, anomalies and forecasted budget risks.
• Partner with Platform Engineering, ML/LLMOps, Infrastructure, Finance and Procurement to implement improvements while maintaining platform performance and reliability.
• Recommend capacity, sourcing and investment decisions, and promote FinOps practices across the organisation.

Requirements

• Bachelor's degree in Computer Science, Engineering or a related discipline.
• At least six years of relevant experience across cloud infrastructure, platform engineering, FinOps, technology cost management or related operations.
• Hands-on experience managing and optimising cloud infrastructure costs, including budgeting, forecasting, allocation and commercial commitments.
• Experience analysing resource utilisation and costs within Kubernetes or OpenShift environments.
• Strong understanding of FinOps practices, including chargeback/showback, anomaly management and unit economics.
• Working knowledge of container resource management, including requests/limits, quotas, scheduling and CPU, memory, storage and GPU utilisation.
• Familiarity with tools such as Kubecost/OpenCost and Grafana, or equivalent cost management and observability platforms.
• Understanding of generative AI cost drivers, including input/output tokens, context size, model serving, routing, GPU utilisation and inference economics.
• Ability to analyse AI consumption and identify optimisation opportunities across prompts, applications, models and endpoints.
• Experience producing dashboards, management reports, procurement analysis and commercial cost models.
• Strong communication skills, with the ability to explain technical cost drivers in business terms and balance cost, performance and reliability.

Interested candidates please reach out to [Confidential Information] with your updated CV. Only shortlisted candidates will be notified.