Sr Product Manager, Opportunity-to-Order

Why You’ll Love This Role

Cribl's growth depends on how reliably we can turn intent into revenue while keeping our systems, data, and teams in sync. The Sr. Product Manager, Opportunity-to-Order (O2O) Systems will partner closely with business stakeholders to shape the roadmap for the systems, workflows, and data that govern how we structure deals, generate quotes, approve commercial terms, set up accurate renewals, and track ARR.

This role sits at the center of Cribl's revenue lifecycle, connecting sales execution, commercial design, and operational scale by owning the systems and data that make quoting, approvals, contracting, and renewals work. It is a high-impact role for someone who likes untangling complex systems, translating abstract revenue and risk questions into clear product direction, and using AI and automation thoughtfully to improve predictability, speed, and confidence across the business.

You will report to the Manager, Product, Enterprise Applications.

As An Active Member Of Our Team, You Will…

• Revenue Systems & AI Strategy: Establish a clear product vision for how Salesforce, DealHub, Ironclad, Clari, and adjacent tools, including AI, work together to support deal design, quoting, approvals, contract workflows, and renewals.
• CPQ Evolution: Guide how DealHub and related CPQ patterns evolve so that complex deal structures, ramps, and subscription changes remain simple for users to configure, price, and approve as Cribl's product mix and commercial models expand, while keeping the experience ready for AI-assisted selling and approvals.
• Revenue Insights & Automation: Strengthen the underlying data models, validation patterns, and integrations across systems so that ARR reporting, forecasting, and AI use cases rest on reliable, well-defined revenue data rather than fragile one-off logic.
• Contracting & CLM Workflows: Influence how Ironclad and Salesforce work together so that contracts, questionnaires, and security artifacts are easy to generate, review, and connect back to the quotes and opportunities they support, structured in ways that unlock AI-assisted review and insight.
• Portfolio Clarity & Stakeholder Partnership: Bring durable structure to a complex program landscape so that stakeholders have a clearer view of how pieces fit together, what is changing, and how those changes affect planning and execution at a strategic level, not just at a ticket level.
• AI Innovation: Create space for well-designed AI experiments with clear hypotheses, guardrails, and success measures, so the business can tell which AI investments are actually improving revenue outcomes and where to scale or pivot.
• Change Management & Long-Term Resilience: Ensure that changes to RLM and CPQ systems, inclu