Strategic Finance Manager

About the Role

This role owns the financial analysis behind our two largest investments: GPU infrastructure and R&D. On the infrastructure side, you'll model how we contract for capacity, how efficiently we use it, and what it costs to serve inference — the drivers that determine gross margin. On the R&D side, you'll partner with Engineering, Product, Security, and IT on headcount planning, tooling and vendor spend, and the operating budget. You'll work directly with leaders across infrastructure, engineering, product, and finance. It's an early to mid-career role with real scope, built for someone with a sharp analytical foundation who wants to understand how the business actually runs and help build the function and processes that enable Fireworks to scale.

What You'll Do

• Own the compute model: Build and maintain the financial model for our GPU fleet — capacity commitments, utilization, cost per GPU-hour — and how all of it flows through to unit economics, gross margin, and cash.
• Support R&D finance: Serve as a finance partner to Engineering, Product, Security, and IT. Support R&D planning end to end: headcount and hiring plans, tooling and vendor spend, and the operating budget.
• Support capacity planning: Serve as a source of truth for what capacity we hold, what we've committed to, and what we're actually using; partner with infra on the plan of record.
• Analyze capacity commitments: Evaluate commitment structures and contract terms with cloud and GPU providers, surface optimization opportunities, and track provider performance and credit refunds.
• Negotiate and manage vendors: Partner on software, tooling, and infrastructure vendor negotiations and renewals, bringing the analysis that gets us better terms.
• Get operational: Sit in infra and engineering planning, learn how utilization, scheduling, and roadmaps actually behave, and bring that reality back into the financial model.
• Forecast and explain: Support forecasting and variance analysis for compute, cloud, and R&D spend on a monthly cadence leadership can rely on, and explain the drivers behind the numbers clearly.
• Split research from production: Track and forecast research and experimentation compute separately from production serving, and build the framework for evaluating return on R&D investment across teams and initiatives.
• Build the function: Establish the reporting, dashboards, and processes that make compute and R&D economics legible to leadership.
• Support the company narrative: Contribute the compute and R&D inputs to board materials, investor updates, and fundraising processes as they come up.

What We're Looking For

• 3–7 years of experience beginning with investment banking, private equity, or equivalent experience — this foundation is required for the modeling and analytical rigor it builds.
• Ideally, subsequent time in a corporate or startup finance seat (strategic finance, FP&A, or corporate development) at a technology company.
• Expert financial modeling skills — you can build from scratch, stress-test your own assumptions, and translate outputs into clear recommendations.
• Genuine interest in operations. You want to understand the physical and technical system underneath the numbers, not just consume its outputs.
• Comfort with messy and imperfect data.
• Excellent communication with technical and non-technical audiences alike — you can take a messy question from a founder or an engineer and return a clear one-page answer.
• Comfortable being both the architect and the operator, with strong instincts for building structure where none exists and building processes to scale.
• High ownership and a bias toward action in an environment where priorities shift and ambiguity is the default.
• Bachelor's degree, or equivalent practical experience.

Nice to Have

• Experience at an AI/ML, developer platform, or cloud infrastructure company, and familiarity with how companies buy and use compute.
• Exposure to cloud, data center, or semiconductor economics — CSP contract structures, capacity commitments, accelerator utilization.
• Experience supporting an engineering organization as a finance partner, including headcount planning and vendor costs.
• Working knowledge of GAAP treatment for infrastructure and capitalized software development costs.
• Experience with consumption- or usage-based revenue models and how commits and tiers are structured around them.
• Proficiency with SQL, Python, BI tools, or an ERP such as NetSuite.
• Enthusiasm for using AI to automate the manual parts of finance work.