Staff AI FinOps & Tokenomics Lead
Core
Establish the discipline, data, and operating model for AI FinOps and tokenomics to answer financial and operational questions about AI capabilities, turning answers into better decisions for UKG's AI portfolio.
Role type
Staff individual contributor (AI FinOps & Tokenomics Lead)
Builds
AI infrastructure economics, cost models, tokenomics frameworks, and executive decision support for AI consumption.
Domain
Cloud FinOps, AI infrastructure economics, product strategy, engineering, finance, and procurement.
Required skills
AI FinOps operating model design, cost modeling for LLMs/inference/agents, tokenomics and cost attribution, forecasting and scenario planning, governance and controls design, executive reporting and storytelling, cross-functional partnership (engineering/finance/procurement), data analytics (SQL/Python/BI), optimization strategies (model selection/routing/quantization), vendor contract management.
Preferred skills
Experience with foundation models, vector databases, retrieval-augmented generation, GPU infrastructure, cloud provider rate structures, self-hosted vs hosted model tradeoffs.
Technologies
LLMs, inference engines, agents, embeddings, vector databases, retrieval-augmented generation, GPUs, cloud billing data, SQL, Python, BI tools.
Responsibilities
Lead the AI FinOps operating model including governance forums and business reviews; build cost models and tokenomics frameworks connecting requests to cost-to-serve; develop bottom-up forecasts and scenario models for AI consumption; establish spend guardrails, budgets, and tagging standards; partner with engineering to optimize model selection and workload placement; build data products and dashboards for AI spend visibility; coach teams on cost-aware design.
Seniority
Staff, trusted advisor to senior leaders