AI FinOps Lead

WeDo Technology Solutions Limited; Croydon; Hybrid; GBP 80,000 - 95,000; Full time

Job summary

WeDo Technology Solutions Limited in Croydon is seeking an AI FinOps Lead to own AI economics and cloud FinOps within a large, complex environment. You will work with engineering, AI and business stakeholders to maximise value from AI investments, while delivering ongoing cost optimisation across cloud usage.

The role focuses on measuring AI consumption, token economics, and ensuring cost efficiency through model selection, caching and cost allocation.

Qualifications

• Proven FinOps experience in complex cloud environments.
• Practical exposure to AI/GenAI cost management and token economics.
• Knowledge of LLM pricing, input/output tokens and caching.
• Experience analysing cloud consumption and turning data into optimisation actions.

Responsibilities

• Take ownership of AI economics and FinOps activity across a complex tech environment.
• Analyse AI, token and cloud consumption to understand where money is being spent and the value generated.
• Work with engineering teams to investigate unusual consumption and identify efficiency opportunities.
• Help teams optimise AI usage through model selection, caching, context management and routing.
• Develop metrics around AI unit economics, token efficiency and value realization.
• Support forecasting and budgeting, flagging overspend early.

Skills

FinOps

AI/GenAI cost

Token economics

Cloud cost analysis

Stakeholder influence

Tools

Azure

Power BI

Job description

Job Title: AI FinOps Lead

Salary: £80,000 – £95,000 + 15% bonus

Location: Croydon – ideally 2 days per week in the office, with some flexibility for the right candidate

Work Type: Permanent

Role: AI investment is growing rapidly, and this is an opportunity to take ownership of how a large, complex organisation manages, measures and maximises the value of that investment. We’re looking for an AI Economics & FinOps Lead to take a highly visible role combining traditional cloud FinOps with the emerging world of AI cost management and token economics. This isn’t a role where you’ll simply produce reports and tell teams what they’ve spent. You’ll work directly with engineering, AI and business stakeholders to understand how AI is being consumed, why costs differ between teams and technology stacks, and whether that investment is delivering genuine business value. You’ll have the opportunity to help shape how AI economics is managed as adoption accelerates, while continuing to drive optimisation across a significant wider cloud estate.

Responsibilities:

• Take ownership of AI economics and FinOps activity across a complex technology environment.
• Analyse AI, token and cloud consumption to understand where money is being spent and the value being generated.
• Work directly with engineering and technology teams to investigate unusual consumption patterns and identify opportunities to improve efficiency.
• Help teams optimise AI usage through areas such as model selection, prompt optimisation, caching, context management and model routing.
• Develop meaningful metrics around AI unit economics, token efficiency and value realisation.
• Support ongoing forecasting and budgeting, identifying potential overspend early and helping teams take action.
• Compare AI models, providers and usage patterns to support better technology and commercial decisions.
• Improve cost allocation, accountability, tagging, showback and chargeback across AI and cloud consumption.
• Continue to drive traditional FinOps optimisation, including rightsizing, commitment utilisation, storage, scaling and workload optimisation.
• Build reporting and dashboards that translate complex consumption data into clear insights for technical teams and senior leadership.
• Become a thought leader for AI economics and FinOps, helping educate teams and establish best practice as the capability develops.

Required Skills:

• Strong experience within FinOps, cloud financial management or a closely related discipline.
• Practical exposure to AI/ML or GenAI cost management and an understanding of token-based consumption.
• Knowledge of how LLM/GenAI pricing and consumption works, including areas such as input/output tokens, caching and different model/provider pricing structures.
• Experience analysing cloud consumption and turning data into tangible optimisation actions and financial outcomes.
• Experience working within a complex cloud environment. Azure is preferred, although experience across other major cloud platforms will be considered.
• Understanding of traditional FinOps practices including cost allocation, tagging, forecasting, budgeting and cloud optimisation.
• Strong analytical and reporting capability, with experience using Power BI or similar tooling.
• The confidence to work directly with engineering leaders, technical teams and senior stakeholders, constructively challenging existing approaches where required.
• The ability to take ownership of a developing capability rather than simply operate within an established process.

Why should I apply?

This is an opportunity to get ahead of where FinOps is going next. You’ll combine an established FinOps skillset with one of the fastest-developing areas in technology: understanding the economics behind enterprise AI adoption. Rather than becoming another person within a large FinOps function, you’ll have the opportunity to become the recognised expert for AI economics and FinOps within the business. The role has significant visibility, with senior stakeholders actively invested in getting this capability right. You’ll be joining at a point where AI investment is accelerating, giving you the opportunity to shape the frameworks, reporting, governance and best practices used to manage it rather than inheriting something already finished. For someone who wants to build their career at the intersection of FinOps, cloud and AI, there is significant scope to develop your expertise, profile and influence as the capability grows.