AI Economics & FinOps Lead

WTW

Greater London

Hybrid

GBP 90,000 - 130,000

Full time

5 days ago

Be an early applicant

Get a reply from this employer

Your resume and cover letter, tailored to exactly what they’re hiring for.

Get past ATS filters

Benefits offered by this job

25 days annual leave

Private healthcare

Life insurance

Group income protection

Health assessments

Defined contribution pension with 10%+

Hybrid working options

Employee assistance programme

Volunteer day

Electric vehicle car scheme

Share scheme

Cycle-to-work

Dental and optical cover

Critical illness protection

Job summary

WTW is seeking an AI Economics & FinOps Lead within its Insurance Consulting and Technology (ICT) line of business. The role focuses on maximising value from AI and GenAI spend through governance and optimisation, while maintaining core FinOps responsibilities for the cloud estate.

The position is hybrid, requiring in-office presence two days per week at the Reigate office. You will drive token economics, reporting, and governance across cloud and AI spend, collaborating with engineering,

Qualifications

Experience in AI/ML or GenAI cost management, incl. token-based consumption models.
Practical FinOps or cloud financial management experience; Azure preferred.
Working knowledge of LLM/GenAI pricing structures across providers.
Experience with token usage monitoring tools.
Knowledge of Azure Cost Management, cost allocation, tagging, forecasting and budgeting.
Ability to translate data into actionable financial insights.
Strong reporting and analytical abilities; attention to detail.
FinOps Certified Practitioner or equivalent is desirable; related AI/cloud certifications are advantageous.

Responsibilities

Be the go-to expert for AI tool and model usage, advising teams on best practices.
Drive cost efficiency by analysing cloud and AI spending and implementing ROI-focused improvements.
Own and evolve the FinOps operating model for AI and cloud assets.
Improve cost allocation, tagging, showback/chargeback and ownership.
Partner with Engineering, Product and Finance to align usage with business goals.
Perform comparative analysis of providers and model tiers for optimal routing.
Develop training and documentation to empower teams to manage resources.
Research new Azure services and AI capabilities for cost optimisation and faster value realization.
Maintain an optimisation pipeline including reservations and savings plans.

Skills

AI/GenAI cost management

FinOps / cloud financial management

Azure

Power BI

Token-based consumption models

LLM pricing structures

Data analysis & reporting

Stakeholder communication

Tools

Azure Cost Management

Power BI

Job description

Description

This job is with WTW, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

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.

Qualifications

Excellent communication and collaboration skills to engage with both technical and non‑technical stakeholders.
Demonstrable experience in AI/ML or GenAI cost management, including token‑based consumption models, together with practical experience of FinOps or cloud financial management. Experience in Azure is strongly preferred.
Working knowledge of LLM/GenAI pricing structures (input/output token pricing, context caching, batch vs. real‑time discounts) across major providers (Azure OpenAI, Anthropic, etc.)
Experience with token usage monitoring or metering tools
Familiarity with performance optimisation practices, such as instance rightsizing, workload optimisation, and model inference efficiency.
Working knowledge of Azure Cost Management, cost allocation and tagging, forecasting and budgeting, and commitment‑based discount management.
Experience translating cloud and AI consumption data into accountable ownership, optimisation actions and measurable financial outcomes.
Strong reporting, problem‑solving and analytical abilities, with attention to detail.
Proven hands‑on experience in Power BI, or similar tools, and data integration techniques.
Ability to translate complex data into clear, meaningful visual insights for technical and non‑technical audiences.
Ability to work independently and drive financial accountability within a dynamic, fast‑paced environment.
FinOps Certified Practitioner or equivalent is highly desirable; AI and cloud certifications, together with practical exposure to AI value tracking, are also advantageous.

What we offer

25 days of annual leave plus an extra WTW day to relax and recharge.
private healthcare
life insurance
group income protection
regular health assessments
defined contribution pension scheme, featuring matched contributions up to 10% from the company.
hybrid working options
employee assistance programme
fully paid volunteer day to make a difference in your community.
electric vehicle car scheme
share scheme
cycle‑to‑work programme
dental and optical cover
critical illness protection