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.
155k – 244k/yr
On-site5+ YOEFinance & Accounting
About the role
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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