Why This Job is Featured on The SaaS Jobs
This director-level remit sits at a core SaaS pressure point: making finance data as reliable and product-grade as customer-facing systems. By centering on auditable pipelines that connect engineering usage signals to enterprise platforms like ERP and planning tools, the role reflects how modern SaaS businesses operationalize revenue recognition, attribution, and close in environments where data volume and system complexity are high. The added emphasis on agentic AI automation signals a finance function that is treating workflow intelligence as part of its systems architecture, not a side project.
For a long-term SaaS career, the role builds durable leverage in domains that travel well across companies: data modeling for financial truth, end-to-end lineage, reconciliation, observability, and SLA ownership for Tier-1 pipelines. Leading multi-disciplinary teams across analytics, data engineering, and AI also develops the operating cadence required to ship platforms that serve many internal stakeholders while meeting compliance expectations.
This is best suited to a senior builder who prefers ambiguous, cross-system problems and can translate finance processes into scalable technical roadmaps. It will fit someone who enjoys partnering with executive stakeholders, setting standards, and making tradeoffs between automation ambition and auditability in production-grade environments.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
We are looking for a Director of Data Engineering and Agentic AI Automation to lead the next generation of our finance data infrastructure. As OpenAI expands its Finance operations, we need scalable and trustworthy data systems to match the pace and complexity of our growth. This includes well-modeled, auditable data for revenue recognition, financial reporting, and planning, supported by reliable pipelines that connect ERP, planning, and operational systems. You will lead a group of analytics engineers, data engineers, and AI engineers to build the data pipelines that connect our internal engineering systems with enterprise platforms such as Oracle Fusion ERP. This role will also define the roadmap for agentic AI automation, enabling intelligent workflows, process automation, and AI-driven decision-making across Finance.
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:
Build and maintain scalable, auditable data infrastructure that powers accurate financial information, with a focus on revenue recognition, compute attribution, and close automation.
Lead and grow teams of analytics engineers, data engineers, and AI engineers to deliver high-impact, intelligent data systems.
Guide work across financial close and allocations automation, B2C revenue automation from engineering systems to ERP (including reconciliation with cash and source systems), and other mission-critical financial processes.
Design and implement data pipelines connecting ERP, planning, and operational systems, including Oracle Fusion, Anaplan, and Workday.
Build and support scalable, audit-proof architecture that enables reliable financial reporting and compliance.
Develop data and AI-powered workflows that enhance forecasting accuracy, compliance automation, and operational efficiency.
Create and maintain data marts and products that support stakeholders across Revenue, FP&A, Tax, Procurement, Hardware Accounting, and Controller teams.
Define and enforce best practices for data modeling, lineage, observability, and reconciliation across finance data domains.
Set the technical direction and manage team structure, mentoring engineers and overseeing contractors or system integrators to ensure delivery of high-quality outcomes.
Partner with senior leaders across Finance, Engineering, and Infrastructure to align on priorities and integrate new automation capabilities.
Ensure data systems are AI-ready and capable of supporting predictive analytics, autonomous agent workflows, and large-scale automation.
Own and maintain Tier-1 data pipelines with strict SLA, data quality, and compliance standards.
Drive the long-term roadmap for agentic AI enablement to build the foundation for “Finance on OpenAI.”
You might thrive in this role if you have:
12+ years in data engineering, with proven experience building and managing enterprise-scale, auditable ETL pipelines and complex datasets
Proficiency in SQL and Python, with demonstrated experience in schema design, data modeling, and orchestration frameworks
Expertise in distributed data processing technologies such as Apache Spark, Kafka, and cloud-native storage (e.g., S3, ADLS)
Deep knowledge of enterprise data architecture, especially within Finance and Supply Chain
Familiarity with financial processes (close, allocations, revenue recognition) and supply chain data models (Supply and demand planning, procurement, vendor master), along with experience in ingesting data from internal engineering systems with large volumes of B2C
Experience integrating with contract manufacturers and external logistics providers is a strong plus
Strong track record of partnering with senior business stakeholders and translating complex requirements into scalable technical solutions
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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