Raspberry AI
Revenue Operations (RevOps)
United States
Sponsorship not specifiedDetected 103 days ago
LLMsStakeholder ManagementHubSpotSalesforceCRMSalesPipeline ManagementOutbound SalesForecastingExcelCustomer SuccessLeadershipCommunicationProblem Solving
About the role
- You'll be responsible for creating structure where it doesn't yet exist-owning CRM, reporting, pipeline hygiene, and core GTM processes-while partnering closely with Sales leadership to enable smarter, faster decision-making.
- This is a hands-on builder role for someone who thrives in early-stage environments and wants to shape how a modern AI company runs its revenue engine.
Responsibilities
- Own and optimize Salesforce (or equivalent CRM) architecture, workflows, and data integrity
- Build and maintain dashboards for pipeline, forecasting, and performance tracking
- Manage integrations across GTM tools (CRM, marketing automation, billing, etc.)
- Partner with Sales leadership to improve pipeline visibility and forecasting accuracy
- Build reporting to track conversion rates, deal velocity, and win/loss trends
- Design and optimize sales processes from lead → close → expansion
- Support territory planning, account segmentation, and ICP definition
- Partner with Sales on deal tracking, inspection, and execution
- Support handoffs between teams (lead routing, onboarding, expansion)
- Identify operational bottlenecks and implement scalable solutions
Requirements
- 4-7+ years of experience in Revenue Operations, Sales Operations, or GTM Operations
- Strong hands-on experience with CRM systems (Hubspot or similar)
- Familiarity with SaaS or usage-based / consumption pricing models
- Strong problem-solving skills and ability to operate in ambiguity
- Builder mindset - you enjoy creating systems from scratch, not just maintaining them
Nice to have
- Experience at a high-growth, VC-backed startup (Series A-C preferred)
Compensation
- Competitive compensation + equity
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This listing is sourced directly from Raspberry AI's careers page and normalized into a canonical job model.