AI FinOps Specialist
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About the Role
About Payoneer
Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.
By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.
We are looking for an AI FinOps Specialist to join our FinOps team and take ownership of AI cost management across the organization.
AI adoption is accelerating LLMs, coding assistants, AI-powered platforms, and API-based services are being consumed across engineering, product, and business teams. This role exists to bring financial governance, visibility, and optimization to that spend before it scales out of control.
You will inherit existing AI cost models and forecasting frameworks, and take them further expanding coverage, improving accuracy, building automation, and working directly with stakeholders to drive cost-aware AI adoption decisions.
This is not a reporting seat. You will own the AI cost domain end-to-end from data collection to executive-level insights to policy enforcement.
What You’ll Do
- Build and own cost visibility across AI vendors and platforms (LLMs, API services, coding assistants, AI-powered SaaS tools)
- Monitor and analyze AI spend by team, use case, and consumption model (token-based, seat-based, usage-based)
- Develop forecasting models for AI costs and usage trends across the organization
- Create dashboards, alerts, and reporting for AI cost tracking and anomaly detection
- Define and enforce AI cost governance policies approval workflows, spend thresholds, usage tiers
- Work closely with engineering, product, and data teams to understand AI usage patterns and influence cost-efficient decisions
- Evaluate and recommend AI cost management tools and platforms
- Benchmark pricing models across AI vendors and support contract negotiations with cost data
- Identify optimization opportunities model selection, prompt efficiency, license right-sizing, consolidation of overlapping tools
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