Enterprise Product Growth Manager

Perplexity • San Francisco, CA

1d • $200,000 - $250,000

About The Position

Perplexity is seeking an Enterprise Product Growth Manager to own the full nurture and engagement engine for their enterprise and business buyers. This role involves managing the entire customer lifecycle from initial contact through expansion, partnering with Demand Generation, Sales, Product Marketing, and Revenue Operations. The ideal candidate will build AI-native tooling to support these programs, demonstrating a proactive and automation-focused approach to marketing. This is not a role for someone who relies on traditional marketing stacks; instead, it's for a marketer who can write SQL, prototype agents, and automate processes.

Key responsibilities include developing and managing enterprise lifecycle user states, building and operating AI-native lifecycle tooling for audience segmentation and personalization, designing multi-channel nurture campaigns, partnering on top-of-funnel outbound strategies, owning post-sale lifecycle management (onboarding, activation, expansion), and running all programs as experiments with a focus on data-driven iteration.

Requirements

• 7+ years in product growth, lifecycle, or growth marketing at a fast-paced startup, with a proven track record of moving activation, retention, and revenue metrics — including enterprise pipeline.
• Experience owning growth end-to-end across the full user journey — from first touch and activation through expansion, monetization, and win-back. You've built growth loops and lifecycle programs that turn signups into engaged users and engaged users into revenue.
• Deep understanding of audience segmentation. You think natively in personas, behavioral triggers, lifecycle stages, and product signals, and you know how to translate that into journeys, experiments, and in-product experiences that actually convert.
• Great taste. You know how to craft copy and experiences that resonate across email, push, and in-product surfaces — for end users, admins, and executives alike — and you can tell the difference between a polished experience and a generic one at a glance.
• Experience and deep interest in building homegrown AI-driven growth engines — programmatic personalization, agentic workflows, and rapid experimentation platforms to scale yourself.
• Builder mentality toward tooling. You don't just operate the modern growth stack (Omni, HubSpot, Loops, Intercom, or equivalents) — you extend it. You've built your own internal tools, scripts, and automated systems to close gaps off-the-shelf software can't, and you'd rather automate a workflow than run it manually twice.
• Comfortable with SQL. You can pull your own cohorts, validate your own segments, and read a dashboard without waiting on a data analyst.
• Operates at high velocity. You ship daily, iterate weekly, and thrive in fast-paced, early-stage environments where processes are still being defined. Urgency is a default setting, not a mode you switch into.

Responsibilities

• Develop and own Perplexity's end-to-end enterprise lifecycle user states — outbound nurture, MQL-to-SQL conversion, opportunity acceleration, post-sale activation, expansion, and renewal — with direct accountability for pipeline created, pipeline progressed, and revenue retained.
• Build and operate AI-native lifecycle tooling — agents that segment audiences from the warehouse, personalize copy at the account and persona level, choose channel and send time, QA before send, and read out results — replacing manual work in our stack wherever it appears.
• Design and run multi-channel nurture across email, in-product, notifications, Slack, and emerging surfaces, tailored to enterprise personas with content tied to where each account sits in the funnel.
• Partner with Demand Generation and Sales on top-of-funnel outbound: turn cold and intent-signaled accounts into engaged conversations, and instrument the handoffs that move them to opportunity.
• Own post-sale lifecycle: admin onboarding, end-user activation, feature adoption, at-risk intervention, and expansion plays that grow seats and ARR inside existing accounts.
• Run every program as an experiment. Define the hypothesis, the control, the primary metric, and the readout. Kill what doesn't work, double down on what does.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed