Responsibilities

• Own the end-to-end lifecycle (Lead → MQL → PQL → SQL → Pipeline) across both PLG and sales-assisted motions, with particular focus on the boundary between them: when does a self-serve user become a sales opportunity, and how do we route them without destroying unit economics or rep efficiency?
• Define and enforce stage definitions, SLAs, and handoff processes. Improve MQL → SQL and PQL → Opportunity conversion rates with a clear-eyed view of which conversions actually create value vs. shift buyers between channels.
• Incorporate product usage signals, free-to-paid behavior, and account-level firmographic data into lifecycle and routing frameworks.
• Identify and resolve funnel breakdowns through data, root-cause analysis, and well-designed experimentation.
• Partner with Data Science to design the methodology for marketing and funnel experiments: clean control groups, incrementality measurement, and experiment designs that produce learnable results.
• Partner with Data and Marketing to ensure that pricing, packaging, and campaign experiments can actually answer the questions they're designed to answer, before they launch.
• Build the instrumentation to measure whether changes in funnel performance reflect real behavior change vs. channel shifting or selection effects.
• Own and optimize our marketing tech stack: HubSpot, Salesforce, ZoomInfo, Clearbit, and attribution tooling.
• Build and maintain workflows, automations, and integrations with strong data quality and governance practices.
• Ship AI-assisted workflows in production: LLM-based enrichment, predictive scoring, intelligent routing. This isn't aspirational; we expect you building and deploying these in your first quarter.

Requirements

• 5+ years in Marketing Operations, Revenue Operations, or GTM Systems in a high-growth SaaS environment running both PLG and sales-assisted motions (not one or the other; both, ideally at the same time with the same product).
• Strong hands-on experience with HubSpot and Salesforce: workflows, automation, custom objects, reporting. You can build it yourself, not just spec it.
• Proven track record building lead lifecycle, scoring, and routing systems, specifically in environments where PLG and sales-assisted motions compete for the same customers.
• Has built or deployed at least one AI/ML-powered workflow in production: predictive scoring, LLM-based enrichment, intelligent routing, or equivalent. We're not looking for "strong curiosity"; we need someone who's shipped it.
• Strong analytical skills. SQL proficiency preferred; at minimum, you can frame questions precisely enough that your data partners can run with them.
• You’re a builder, not a spec writer. You drive work forward without waiting for permission, you're direct when something isn't working, and you close the gap between what you build and the impact it creates. You're curious enough to learn the business context behind the systems you own, empathetic enough to earn trust across Sales, Data, and Marketing, and scrappy enough to ship before it's perfect. You bring energy and intellectual curiosity to the work, not just competence