Revenue Systems Lead, Data Infrastructure

About the Team

OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission.

The Revenue team plays a critical role in enabling OpenAI to scale its commercial offerings – overseeing billing operations, deal desk, revenue systems, and revenue accounting. We work cross-functionally with Product, Engineering, and Go-To-Market teams to support new monetization strategies, improve operational efficiency, and maintain financial integrity.

About the Role

We’re seeking an experienced Revenue Systems Data Infrastructure Lead to drive the evolution of our billing infrastructure and monetization platform. In this role, you’ll own the roadmap and execution strategy for foundational systems that power our pricing, billing, and revenue data workflows. You’ll help ensure our data infrastructure is scalable, resilient, and adaptable to support a dynamic and fast-growing revenue team needs.

You’ll serve as a key partner to Engineering, Product, and Finance teams in shaping systems architecture, supporting critical launches, and aligning infrastructure with our long-term strategic goals.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Serve as the central point of leadership aligning Finance, Product, and Data Engineering teams on data and automation priorities, establishing the core revenue data vision and automated controls needed for reliable revenue recognition, scalable analytics, and compliant financial operations.

• Drive automation of process, controls and reporting of revenue transactions through deep understanding of required data elements, spanning GTM systems, ERP, monetization engines, and payment and payout systems.

• Work across financial close and allocations automation to drive revenue automation and connect internal engineering systems to ERP (including reconciliation with cash and source systems), and other mission-critical revenue financial processes.

• Define and support scalable, audit-proof reporting and controls that enable reliable financial reporting and compliance.

• Partner with Engineering to develop AI-powered workflows that enhance financial accuracy, transaction tracing, recons, compliance automation, and operational efficiency.

• Partner with Engineering to define revenue requirements to drive design of data marts, dashboards and analysis tools that support finance stakeholders across Revenue and Controller teams.

• Define and enforce best practices for data infra, lineage, observability, and reconciliation across finance data domains.

• Partner with senior leaders across Finance, Data Engineering, and Product to align on priorities and integrate new automation and data capabilities.

You might thrive in this role if you have:

• 12+ years of experience in streamlining and automating Revenue Systems, Billing Infrastructure, Revenue Accounting, and Financial Data Modeling to support the business, ideally within high-growth or public-company environments.

• Proven track record leading cross-functional system implementations and partnering with Finance, Engineering, and Product teams to scale and operationalize billing architecture.

• Exceptional communication skills with the ability to drive alignment, influence decisions, and advocate for data infrastructure needs across technical and non-technical audiences.

• Expert in financial processes (close, allocations, revenue recognition), along with experience in defining critical data elements to implement both within ERP and internal engineering systems and ability to help process and reconcile large volumes of B2C and payment transaction data.

• Expert in data infra design, data governance and controls and best practices — with experience in SQL, reconciliation processes, and financial system reliability.

• Excitement to work at the intersection of finance, data, systems, and emerging technologies in a fast-paced environment.

• Proven success leading complex data and system initiatives, from roadmap definition to execution, with deep cross-functional alignment.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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