Revenue Operations Lead

Relevance AI Pty Ltd

Job Overview

Location

San Francisco, United States

Job Type

Full-time

Full Job Description

📋 Description

• Own and optimize the go-to-market tech stack including HubSpot, Outreach, Apollo, quoting tools, and Relevance AI agents to ensure systems are well-governed, integrated, and delivering measurable ROI.
• Build reliable revenue reporting and dashboards that provide leadership and investors with a clear, accurate view of business performance.
• Design and improve lead management, pipeline hygiene, forecasting, and territory processes to scale with the company’s growth.
• Manage and develop AI agent infrastructure across the GTM function, collaborating with teams to automate manual workflows and drive productivity.
• Partner with Sales, Marketing, Customer Success, and Finance leaders to scope problems, present clear options, and execute solutions from inception through ongoing iteration.
• Administer HubSpot at scale, including building workflows, automations, and understanding CRM architecture deeply to support commercial operations.
• Apply systems thinking with a long-term view, designing processes that remain effective six months after launch and prioritizing ROI and success indicators.
• Translate commercial metrics that matter to sales leaders, founders, and investors into trusted reporting frameworks that drive action.
• Influence cross-functionally without authority by clearly presenting trade-offs, demonstrating sound judgment, and aligning stakeholders around data-driven decisions.
• Operate in a high-growth B2B SaaS environment with a collaborative approach, sharing context freely and making teammates more effective.
• Solve complex operational problems by breaking them down, presenting structured options with clear trade-offs, and seeing solutions through to completion.
• Embrace AI-driven operations as a core part of the role, bringing curiosity and a willingness to learn rather than requiring prior AI experience.
• Function effectively in a startup or scale-up setting, comfortable with ambiguity, capable of building from first principles, and experienced as a solo operator or in a small team.
• Contribute to shaping the future of Relevance AI’s culture, ways of working, and benefits as an early team member with direct impact on company direction.

🎯 Requirements

• 4+ years in RevOps, Sales Operations, or GTM Operations in a high-growth B2B SaaS environment
• Hands-on HubSpot expertise including administration, workflow building, and deep understanding of CRM architecture
• Systems thinking with a long-term view, prioritizing sustainability and ROI beyond initial implementation
• Commercial acumen to understand and build reporting around metrics that matter to sales leaders, founders, and investors
• Strong communication and influencing skills to drive alignment without authority
• Startup or scale-up experience with comfort in ambiguity and ability to build from first principles

🏖️ Benefits

• Health Insurance Contribution for medical, dental, and vision coverage
• Commuter Benefits with pre-tax deductions for transit and parking
• Unlimited Annual Leave policy
• ESOP (Employee Stock Ownership Plan)
• AI Productivity Benefit of up to $1,200 USD/year for AI tools, courses, and learning resources
• 12 weeks of paid parental leave for all eligible new parents, plus an additional 6 weeks for the birthing parent
• Team lunches every Tuesday, Thursday, and Friday, plus Uber Eats dinners and regular catered office meals
• Free breakfasts, healthy snacks, and fully stocked fridge of drinks
• Quarterly team events for bonding and connection
• Social clubs for hobbies such as hiking, chess, board games, and social committee activities
• Milestone Merch for work anniversaries with customized Relevance AI swag

Skills & Technologies

REST

Senior

Hybrid

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Relevance AI Pty Ltd

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About Relevance AI Pty Ltd

Relevance AI offers a low-code platform that lets teams build, deploy and manage AI agents and workflows at scale, integrating vector search, embeddings and LLM tooling into existing data stacks without heavy infrastructure work.

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