Enterprise Product Growth Manager

Perplexity Perplexity · AI Frontier · San Francisco, CA · Growth

This role focuses on building and operating AI-native tooling and agentic workflows to automate and personalize the enterprise customer lifecycle, from initial contact through expansion and renewal. The ideal candidate has a builder mentality, is comfortable with SQL, and has experience in product growth or lifecycle marketing at a fast-paced startup.

What you'd actually do

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.

Skills

Required

  • 7+ years in product growth, lifecycle, or growth marketing
  • proven track record of moving activation, retention, and revenue metrics
  • Experience owning growth end-to-end across the full user journey
  • Deep understanding of audience segmentation
  • Experience and deep interest in building homegrown AI-driven growth engines
  • Builder mentality toward tooling
  • Comfortable with SQL

Nice to have

  • writes their own SQL
  • prototypes their own agents
  • treats every flow as something to automate rather than execute by hand

What the JD emphasized

  • AI-native tooling
  • build homegrown AI-driven growth engines
  • agentic workflows
  • automate a workflow

Other signals

  • AI-native tooling
  • build homegrown AI-driven growth engines
  • agentic workflows
  • programmatic personalization
  • automate workflow