Senior Manager of Financial Cloud & AI Operations

Thought Spot is a Data & AI platform that helps companies turn data into enterprise advantage. We're Gartner MQ leaders with more than 1,000 customers globally and offices in Mountain View, Chicago, London, Bangalore, Sydney, and Tokyo.

Thought Spot is hiring a Senior Manager of Financial Cloud & AI Operations to own the financial side of planning, modeling, and contracting for our cloud, token, and AI resources. This role is central to managing cash flow and building a profitable portfolio of AI-native cloud products. You’ll partner with Engineering, Dev Ops, Business Analytics, and Financial Planning, and work directly with C-level executives.

Reports in to Finance team.

Usage patterns, product adoption, model mix, and vendor economics in this space change fast. You’ll turn complex data into clear recommendations, and know when a decision needs deep analysis and when the business needs a timely directional answer.

• AI and cloud financial planning: Partner on forecast and scenario modeling for cloud, GPU, and token spend. Tie usage, adoption, model mix, and vendor pricing to COGS and gross margin. Monitor spend against budget, establish variance thresholds, and intervene proactively on unplanned consumption spikes.
• GPU and capacity forecasting: Partner with Engineering leadership to establish a unified demand forecast across production inference, internal research, and new product development, translating compute demand into prioritized spend and capacity plans.
• Vendor commitments and rate optimization: Model and manage commitments. Evaluate break-even horizons, stranded-commitment risks, and optimal terms for RIs, Savings Plans, CUDs, Provisioned Throughput Units (PTUs), dedicated instance hosting, and token drawdowns. Support contract negotiations with Procurement and Finance leadership.
• AI product economics: Build unit economics models for AI products and act as the finance partner to Product and Pricing, ensuring consumption-based pricing preserves gross margin targets.
• Fin Ops governance and reviews: Run the allocation standards, controls, and review cadence that keep cost in check while enabling adoption. Lead recurring reviews with the highest-consuming teams.
• Efficiency KPIs and savings accountability: Define operational efficiency metrics with Engineering (e.g., cluster/GPU utilization rates, cost per query, cost per million tokens). Track engineering cost‑reduction commitments from initial sizing to realize billing impact, and elevate misses to leadership.
• Reporting, tooling, and C-suite visibility: Partner with Data Engineering and BI to operationalize trusted multi-cloud datasets, automated allocation pipelines, and AI-driven anomaly detection. Deliver executive-ready financial reporting, risk assessments, and strategic recommendations directly to the CFO, CTO, and executive leadership.

• 7+ years in financial modeling, driver-based forecasting, scenario analysis, and budgeting at an AI, SaaS, or other technology company.
• 3+ years of Cloud and AI economics:
  Working knowledge of cloud pricing and billing models (reserved vs. on-demand, commitments, CUR exports).
• Analytical judgment: You can pull the few variables that matter out of large, messy datasets and turn them into clear recommendations.
• Systems: Expert-level Excel, SQL knowledge, plus hands‑on experience with BI tools, Fin Ops tooling, and cloud cost analysis tools.
• AI-driven finance: You’ve used or evaluated AI tools to improve forecasting or reporting.
• Leadership: Experience working on a globally distributed team.
• Communication: You simplify complex financial and technical topics and produce polished, executive-ready deliverables.
• Education: Bachelor’s…