Finance Operations Lead AI

Overview

In this Finance Operations Lead role, you will maximise the business value of AI and GenAI investments through governance, cost optimization, and value measurement, while maintaining FinOps across the cloud estate. You’ll act as the AI and model consumption SME, guiding teams on best practices and translating usage data into accountable actions and financial outcomes. Collaborating with Engineering, Product and Finance, you’ll drive efficiencies like prompt optimization and model routing to balance cost and outcomes. You’ll shape AI FinOps frameworks and reporting that track unit economics and forecasts, contributing to scalable, data-driven decision making.

Pay / Benefits

• Hybrid working
• Enhanced parental leave
• 25 days holiday + buy days + birthday off
• Pension up to 10%
• Health Care and Life Assurance
• Training and career development

Responsibilities

• Maximise business value from AI/GenAI investments via governance, consumption optimization, unit economics and value measurement
• Maintain FinOps responsibilities across the wider cloud estate
• Be subject matter expert for AI and model consumption, advising teams on best practices
• Analyse cloud and AI spend, improve cost allocation and establish governance, controls and standards
• Collaborate with Engineering, Product and Finance to identify opportunities to reduce consumption without compromising outcomes
• Apply techniques like prompt optimisation, context management, caching, model routing and batching
• Evaluate LLMs and provider pricing to inform cost-effective technology decisions
• Develop AI FinOps and Token Economics frameworks, with dashboards and reporting for AI unit economics, token efficiency, forecasts and value-realisation metrics
• Manage budgeting, forecasting and variance analysis; maintain an optimization pipeline across AI consumption and traditional cloud levers (rightsizing, reservations, storage, scheduling)
• Assess FinOps maturity, research new Azure and AI capabilities, and develop training/documentation
• Engage with stakeholders at all levels to drive continuous improvement

Key requirements

• Experience in AI/ML or GenAI cost management including token-based consumption models
• Practical experience of FinOps or cloud financial management
• Experience with token usage monitoring or metering tools
• Familiarity with performance optimization practices (rightsizing, workload optimization, model inference efficiency)
• Knowledge of Azure Cost Management, cost allocation and tagging, forecasting and budgeting
• Ability to translate cloud and AI consumption data into accountable ownership and measurable outcomes
• Strong reporting, problem solving and analytical abilities
• Ability to translate complex data into clear visual insights for technical and non-technical audiences
• Advanced collaboration, communication and influencing skills

• collaboration
• communication
• influencing
• AI/ML cost management
• FinOps
• token usage monitoring tools

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