Director, Tokenomics & FinOps Engineering

Position Summary

The Director, Tokenomics & FinOps Engineering is responsible for building and leading AI economics capability while establishing the engineering foundation required to support scalable FinOps and Tokenomics execution.

This role owns AI cost transparency, tokenomics, AI forecast management, unit economics, AI spend analytics, cost-control frameworks, and the underlying data, reporting, and engineering capabilities that make those functions possible.

The Director will partner closely with Finance, Engineering, Architecture, AI platform teams, and technology leadership to provide visibility, accountability, forecasting, and executive decision support for enterprise AI investments.

U.S. business hours required.

Key Responsibilities

AI Tokenomics & Technology Economics

AI Cost Transparency

• Establish enterprise standards for AI spend visibility.
• Develop token consumption reporting and analytics capabilities.
• Create dashboards and reporting for AI platform usage and costs.
• Provide transparency into AI consumption trends across platforms and use cases.

AI Forecasting & Economics

• Develop forecasting models for AI spend, token consumption, and platform growth.
• Establish AI unit economics frameworks and cost attribution methodologies.
• Support annual planning and budgeting processes for AI investments.
• Analyze emerging AI pricing and consumption trends.

AI Cost Controls

• Develop frameworks for AI cost control and consumption governance.
• Establish economic guardrails, thresholds, and escalation triggers.
• Support integration of cost controls into AI development and deployment processes.
• Monitor and report on adherence to established economic controls.

Executive Decision Support

• Deliver executive reporting and AI economics dashboards.
• Support technology investment planning and prioritization discussions.
• Develop financial insights that enable informed AI investment decisions.
• Present consumption trends, forecasts, and recommendations to senior leadership.

FinOps Engineering

Data Quality & Financial Data Management

• Lead initiatives to improve financial data quality and integrity.
• Partner with technology teams to strengthen attribution and reporting capabilities.
• Establish standards for cloud and AI financial data management.

CMDB & Tagging Enablement

• Drive improvements supporting cloud and AI cost attribution.
• Partner with application and platform teams on tagging standards and implementation.
• Improve asset-to-application mapping capabilities needed for financial reporting.

Automation & Reporting Engineering

• Lead automation efforts that reduce manual reporting and analysis activities.
• Develop scalable reporting architectures and data pipelines.
• Enhance Power BI, Cloudability, and related reporting capabilities.
• Establish engineering practices to support future reporting growth.

Application Cost Transparency

• Support application-level financial visibility and technology cost attribution.
• Improve reporting alignment across cloud, AI, and application portfolios.
• Enable technology investment visibility through improved data foundations.

Required Qualifications

• Bachelor's degree in Finance, Accounting, Business Administration, Information Technology, Computer Science, or a related discipline.
• 8+ years of experience in FinOps, technology economics, technology finance, data engineering, analytics, or related fields.
• Demonstrated experience working with AI consumption models, cloud economics, or technology financial governance.
• Demonstrated experience working with enterprise-wide FinOps, cloud cost management, technology financial governance, or optimization initiatives.
• Experience leading reporting, analytics, data engineering, or financial transparency programs.
• Strong understanding of forecasting, unit economics, and financial modeling.
• Experience building scalable reporting and automation capabilities.
• Proven ability to lead cross-functional initiatives across Finance, Engineering, Architecture, and Technology organizations.

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