Senior AI FinOps Engineer

About the role

The Senior AI FinOps Engineer owns the FinOps framework for a client's AI platform, giving visibility and control across cloud, on-premises OpenShift, GPU infrastructure and GenAI token consumption. The role drives sustainable unit economics while keeping application performance high and supports informed investment, capacity and sourcing decisions. It sits at the intersection of platform engineering, ML/LLMOps, IT infrastructure, finance and procurement.

Key responsibilities

• Own and maintain the centralised FinOps framework tracking cloud, OpenShift, GPU infrastructure and GenAI token consumption across projects, teams and applications.
• Drive GenAI token cost optimisation through model selection, routing, caching, prompt and token efficiency, usage controls and cost-per-request analysis.
• Optimise OpenShift consumption via right-sizing, utilisation analysis, workload scheduling, quota management and identification of under-utilised resources.
• Drive cloud cost optimisation across Azure services through right-sizing, reservations and commitments, workload scheduling, storage optimisation and removal of idle resources.
• Set up chargeback and showback models, tagging, cost allocation and governance standards for accurate project attribution.
• Administer budgets, including forecasting, variance analysis and regular management reporting.
• Support procurement activities: demand forecasting, quotation evaluation, commercial analysis, contract and commitment planning.
• Build dashboards, alerts and unit-cost metrics to monitor actual and forecast spend, utilisation and token cost.
• Identify budget risks and cost anomalies through ongoing monitoring.
• Partner with platform engineering, ML/LLMOps, IT infrastructure, finance and procurement teams to implement cost optimisation without compromising performance.
• Advise management on investment, capacity, sourcing and cost optimisation decisions.

Required profile

• Bachelor's degree in Computer Science, Engineering or a related field.
• At least six years of experience in cloud infrastructure, platform engineering, FinOps, technology cost management or related operations.
• Experience in technology budgeting, procurement analysis, vendor quotations and commercial or cost modelling.
• Experience partnering with finance, procurement and engineering teams on budgets and cost optimisation.
• On-site working arrangement.

Required skills

• Cloud FinOps: budgeting, forecasting, cost allocation, chargeback/showback, anomaly management and unit economics.
• Kubernetes or OpenShift resource management (CPU, memory, storage, GPU, requests, limits, quotas, scheduling).
• Cost management tools such as Kubecost or OpenCost.
• Observability platforms such as Grafana, including dashboard and report development.
• Understanding of GenAI and LLM cost drivers (tokens, model serving, GPU utilisation, context size, model routing, inference economics).
• Strong communication skills to explain technical cost drivers in business terms.