Here at GXO, we’re looking for a Cloud FinOps Engineer to join our team. You’ll play a key role in driving cloud financial management, helping to optimise cloud spend while ensuring performance, scalability, and business value.
The Cloud FinOps Analyst is responsible for monitoring, analysing, reporting, and helping optimise GXO’s cloud consumption costs across Google Cloud, AWS, Azure and AI-enabled services. The role provides visibility of actual spend, forecasts, budget variance, anomalies, key cost drivers and AI token usage.
This is a full-time permanent position. You’ll be working Monday to Friday, 09:00 till 17:00 with occasional travel to our Northampton or London office. However, some flexibility is required, this is logistics after all!
What you’ll do on a typical day:
- Own cloud cost management and financial visibility across AWS, Azure and Google Cloud, delivering accurate reporting, forecasting and strategic insights that help GXO optimise spend while supporting innovation and growth.
- Lead AI expenditure and usage analysis, providing transparency into model, API, token and agent consumption to ensure AI services are delivered cost-effectively and aligned to business value.
- Champion FinOps best practice through effective cost allocation, show back and chargeback mechanisms, partnering with technology and finance stakeholders to improve accountability and cloud financial governance.
- Identify trends, risks and optimisation opportunities through forecasting, budgeting and anomaly detection, helping to control expenditure, improve efficiency and maximise return on cloud and AI investments.
What you need to succeed at GXO:
- Strong experience in a FinOps Cloud Engineering role, with strong hands-on delivery experience
- Experience in cloud cost management, FinOps, technology financial management, cloud operations, data analysis or FP&A
- Experience producing dashboards, monthly cost packs, budget variance analysis, forecasting reports, anomaly analysis and executive summaries.
- Cloud fundamentals or practitioner-level certification in Google Cloud, AWS or Microsoft Azure desirable.