Enterprise Product Manager - AI Solutions

OpenAI
San FranciscoPosted 25 April 2026

Job Description

Enterprise Product Manager - AI Solutions ABOUT THE TEAM The Enterprise Platform Technology team builds and operates the platforms and integrations that run the company’s core business workflows across Finance, People, Procurement and GTM. We deliver secure, scalable system connectivity and AI-native experiences that reduce manual work, strengthen controls, and improve operational reliability across the enterprise stack. ABOUT THE ROLE As an Enterprise Product Manager, AI Solutions, you will identify, shape, and scale AI-enabled products and workflows for core enterprise functions, with an initial emphasis on Finance. You will partner with Finance, Enterprise Platforms Engineering, People and other enterprise teams to translate operational pain points into practical AI solutions, from copilots and agentic workflows to data products and system automations. This is an individual contributor role with broad cross-functional leadership: you will define the roadmap, prioritize high-impact use cases, run structured experiments, drive delivery across technical and non-technical teams, and measure adoption and business value. You will help turn fragmented tools, data, and processes into cohesive AI solutions that are secure, reliable, and usable in the real world. You will work hands-on with leading ERP, HCM, CRM, planning, ticketing and data platforms (e.g., Oracle, Workday, Salesforce, Databricks, etc.), along with our own internal products and platforms, ensuring solutions are grounded in the realities of data quality, controls, governance, and operational ownership. We’re looking for people who can move fluidly from understanding business process needs to defining product requirements and collaborating with internal product teams to improve solutions for our users. 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: - Identify and prioritize AI-driven opportunities to automate finance operations and adjacent enterprise workflows, enabling more efficient processes, better insights, and stronger execution. - Partner with stakeholders to understand current-state processes, pain points, data dependencies, risk constraints, and success metrics, then translate those into clear product requirements and prioritized roadmaps. - Define product requirements and develop lightweight prototypes to help guide engineering teams in building solutions that meet user needs. - Design and lead pilots for AI-enabled workflows, including agentic tools, workflow automation, and custom applications, with clear hypotheses, rollout criteria, and measurable outcomes. - Collaborate with Enterprise Platform Engineering and internal platform teams to adopt OpenAI technologies, such as Codex, as well as MCP-based actions and connectors that securely expose enterprise system capabilities to AI workflows. - Coordinate secure data onboarding and integration across systems such as Oracle, Workday, Salesforce, Anaplan, Databricks, and external vendor platforms, partnering with data owners, IT, Security, Legal, and Risk as needed. - Own delivery across technically and organizationally complex initiatives, aligning requirements, dependencies, and governance reviews, so teams can move from experimentation to scaled adoption. - Track adoption, quality, and business impact through dashboards, user feedback, and executive-ready updates, and use those signals to iterate on product direction and investment priorities. - Assist with other development efforts as needed. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have 8+ years of experience across product management, enterprise applications, business systems, or enterprise transformation, with a track record of driving technology-enabled business outcomes in complex environments. - Bring strong fluency in Finance processes and enterprise technology, with experience across areas such as quo ... (truncated, view full listing at source)
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