Responsibilities
- Owns and drives the full planning cycle—annual operating plans, quarterly forecasts, rolling projections, and long-range strategic planning tailored to AI research timelines (spoiler: annual budgets don't work)
- Builds sophisticated financial models covering multiple revenue streams (API, Enterprise, Playground), GPU compute economics, headcount planning, and cash flow across US and German entities
- Delivers monthly and quarterly business reviews with variance analysis, KPIs, and actionable insights that support executive planning and board reporting
- Leads scenario planning for decisions most companies don't face: GPU provider contracts, go-to-market expansion, pricing frameworks, and R&D investment allocation where one breakthrough hire might 10x capabilities
- Partners with GTM leadership on revenue forecasting when your 'pipeline' includes researchers, startups, and Fortune 500s with completely different economics
- Collaborates with Engineering on GPU compute optimization and infrastructure planning where the input is 'we need more GPUs' and your job is figuring out how many, when, and from which providers
- Builds executive dashboards tracking what actually matters: ARR growth, customer cohort economics, gross margins, burn rate, and the relationship between model quality and infrastructure cost
- Designs scalable FP&A processes and drives automation across financial planning—working with Accounting to ensure data integrity and reporting consistency
- Supports high-impact strategic initiatives: pricing optimization, enterprise contract structuring, customer segmentation economics, and fundraising support.
Requirements
- 6-10 years in FP&A, corporate finance, investment banking, or strategic finance, with at least 4 years hands-on FP&A experience at a high-growth company
- Proven track record owning full planning cycles (annual budgeting, quarterly forecasts, long-range planning) at a B2B SaaS, AI, or technology company
- Advanced Excel/Google Sheets modeling skills—you build complex financial models from first principles, not templates
- Fluency in SaaS metrics (ARR/MRR, NDR, CAC, LTV, payback period, gross margin, Rule of 40) and ideally consumption-based pricing models
- Experience with modern finance tech stack and genuine curiosity about AI-powered finance workflows versus legacy systems
- Comfort with international operations, multi-entity financial structures, and US GAAP
- Ability to work with large datasets, perform deep variance analysis, and build dashboards that executives actually use.
Nice to Have
- Experience with usage-based or consumption revenue models, API pricing structures, or GPU/cloud infrastructure economics
- Understand subscription economics alongside usage-based pricing in technical or developer-focused markets
- Bring exposure to enterprise contract structuring and technical sales processes
- Have worked somewhere that scaled 3-5x and had to rebuild planning processes mid-flight
- Intellectually honest about uncertainty—you can say 'here's what we don't know yet' without flinching.
Additional Information
- We’ll cover reasonable travel costs to make this possible.
