AI Economics & FinOps Lead
WTW · Reigate
This is an exciting opportunity to join as an AI Economics & FinOps Lead within the Insurance Consulting and Technology (ICT) line of business. The primary focus is to maximise the business value of AI and GenAI expenditure through active governance, consumption optimisation, unit economics and value measurement, while retaining core FinOps responsibility for the wider cloud estate. The role will provide insightful reporting and analytics, improve financial accountability and ensure token-based consumption is actively governed and optimised.
This position is hybrid working, with a requirement to be in office two days a week in the Reigate office.
At WTW, we believe difference makes us stronger. We want our workforce to reflect the different and varied markets we operate in and to build a culture of inclusivity that makes colleagues feel welcome, valued and empowered to bring their whole selves to work every day. We are an equal opportunity employer committed to fostering an inclusive work environment throughout our organisation. We embrace all types of diversity.
The Role
You will be the go-to expert for AI tool and model usage, advising teams on best practices and optimisation strategies, while leading the Token Economics working group and supporting the wider FinOps operating model across cloud and AI spend.
Drive cost efficiency by analysing cloud and AI spending, identifying areas for improvement, and implementing solutions that maximise return on investment and business value.
Own and evolve the FinOps operating model for AI and the wider cloud estate, establishing clear standards, governance, accountability and decision rights.
Improve cost allocation, tagging, showback or chargeback and ownership so that cloud and AI consumption can be attributed to accountable products, platforms and business teams.
Partnering with Engineering, Product and Finance to align cloud and AI usage with business goals, and drive cloud-related strategic initiatives inc. token-efficiency techniques such as prompt optimisation, context-window management, caching, model tiering/routing, and batching - to reduce consumption without degrading outcomes
Comparative analysis of LLM/model across providers and tiers, to inform model selection and routing decisions.
Provide comprehensive training and documentation to empower teams to manage their own cloud resources effectively.
Continuously research and evaluate new Azure services and AI platform capabilities to identify opportunities for innovation, cost optimisation and faster value realisation.
Maintain a balanced optimisation pipeline covering AI consumption and traditional cloud levers, including reservations and savings plans, commitment utilisation, rightsizing, storage, scaling and workload scheduling.
Develop and implement AI FinOps and Token Economics frameworks, including policies, controls, processes and best practices covering AI governance, model lifecycle costs, token economics and alignment with the wider cloud FinOps operating model.
Create metrics, financial dashboards and reports that provide insights and forecasts to technical teams and senior leadership, including AI unit economics, token usage efficiency, and value-realisation KPIs.
Lead cloud and AI forecasting, budgeting and variance analysis, providing actionable recommendations to improve planning accuracy and control unplanned expenditure.
Conduct regular FinOps maturity assessments across AI and cloud workloads, maintaining a prioritised roadmap for governance, optimisation and continuous improvement.
Stay updated with the latest trends and best practices in cloud cost management and AI cost governance
Communicate effectively with stakeholders at all levels, including leadership.