Director, Financial Systems
Lead FinOps strategy and cloud financial governance across GCP and AWS. Manage AI cost frameworks, vendor negotiations, forecasting, and build a cost-conscious engineering culture.
What You'll do
- Global Cloud Governance: Lead the centralized FinOps strategy across an international multi-cloud footprint, focusing heavily on GCP and AWS optimization.
- Unit Economics Modeling: Design and maintain sophisticated cost-allocation frameworks for all shared cloud resources, translating complex multi-tenant consumption into transparent, actionable product margins.
- AI Economic Stewardship: Manage the financial impact of our AI roadmap. Oversee current model consumption costs and build the fiscal framework for the transition into building and training custom models.
- Forecasting & Tooling Ownership: End-to-end management of cloud budgets and third-party hosting licenses, leveraging variance analysis and capacity planning to translate dynamic engineering metrics into predictable, accurate financial forecasts.
- International Vendor Management: Act as the primary lead for global vendor relationships. Drive enterprise negotiations, contract renewals, and strategic partnerships to maximize value across different international regions.
- Strategic Reporting: Partner with Finance and Engineering leadership to provide "Cloud TCO" visibility, leveraging both industry-standard platforms and custom in-house tooling.
- Team Leadership: Lead the development of the FinOps team, mentoring and fostering their technical growth and career progression.
What you bring
- 5+ years in technology operations, procurement, or cloud finance, with at least 2–3 years of experience in a formal people management or leadership role.
- Demonstrated ability to bridge the gap between Finance, DevOps/SRE, R&D and Product teams, fostering a cost-conscious engineering culture without bottlenecking innovation or deployment speed.
- Proven experience with production-grade environments in GCP and AWS, including deep knowledge of billing, commitment models, and discount structures.
- Deep technical expertise across modern cloud ecosystems, including Kubernetes resource management, serverless compute, storage lifecycle tiering, and managed databases with a proven ability to translate complex architectural configurations into optimized unit economics.
- A track record of operating successfully in a decentralized management structure, negotiating high-value, international contracts with major technology providers.
- Familiarity with the cost drivers of AI, from API consumption tokens to the compute-intensive requirements of model training.
Abilities Required
- Ability to manage expectations and prioritize work across multiple "customer" teams and Engineering Managers.
- Comfortable leading through a broad range of technologies and shifting priorities as we move from AI consumption to model building.
- Strong analytical skills with the ability to provide a "safety net" during complex architectural shifts or cost anomalies.
- Must be able to maintain high-bandwidth communication with global leadership and peers over textual mediums and video conferencing.
- Exceptional presentation/leadership skills, concise and fluent communication.
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