Sr Product Manager, Opportunity-to-Order

Cribl

2h•Remote

About The Position

Cribl is a rapidly growing, remote-first company that provides the data engine for IT and Security. We are looking for collaborative, curious, and motivated team members who are passionate about putting customers first. As the Sr. Product Manager, Opportunity-to-Order (O2O) Systems, you 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 high-impact role sits at the center of Cribl's revenue lifecycle, connecting sales execution, commercial design, and operational scale. You will untangle complex systems, translate abstract revenue and risk questions into clear product direction, and use AI and automation thoughtfully to improve predictability, speed, and confidence across the business. You will report to the Manager, Product, Enterprise Applications.

Requirements

5+ years of progressive product management in B2B SaaS, with direct ownership of revenue, CPQ, or opportunity-to-order systems and the stakeholder complexity that comes with them.
Hands-on experience with modern CPQ (DealHub, Salesforce CPQ, or similar) in a Salesforce Sales Cloud environment, with a strong understanding of how quoting, approvals, subscription management, and renewals connect across the revenue lifecycle.
Demonstrated history of defining and shipping AI use cases in internal business workflows, not only prototypes, including the judgment to know where AI is helpful and where it is not.
Strong understanding of opportunity stages, quoting and approvals, discounting patterns, renewals, and ARR or revenue modeling in a modern SaaS business.
Comfort reasoning about how data flows through integrated systems, including how field definitions, ARR logic, and integration design affect both day-to-day operations and the reliability of inputs to AI and analytics.
Proven ability to build strong relationships across a wide set of stakeholders with differing priorities and vocabulary to align product initiatives with broader company goals.
Experience using data and metrics to assess product impact, define success, and make the case for continued investment or course correction.
Able to work effectively with engineering systems teams, translating business requirements into product direction, surfacing implementation tradeoffs, and writing clear acceptance criteria.
Exceptional written and verbal communication skills, with the ability to make complex systems, AI concepts, and tradeoffs understandable to a wide range of audiences.

Nice To Haves

Experience with DealHub or another modern CPQ solution in a Salesforce-centric environment.
Experience with Salesforce-centric integrations supporting opportunity, quote, and renewal flows and their reporting needs.
Familiarity with Ironclad and CLM patterns that connect contracts back to Salesforce opportunities and quotes.
Exposure to IT general controls (ITGC) requirements and how O2O patterns intersect with those needs.
Experience building or scaling agentic workflows or AI-assisted automations for revenue, sales, or legal teams.
Comfort working in a high-growth, remote-first environment.
Curiosity about practical AI in internal business systems.
A sense of humor, and a love for goats.

Responsibilities

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.
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.
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.
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.
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.
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.
Ensure that changes to RLM and CPQ systems, including large initiatives and incremental AI and automation work, are introduced with the right discovery, design, testing, UAT, deployment, and hypercare patterns so improvements are stable in production and sustainable as Cribl's business evolves.