Full Job Description
Demand Generation Lead to join our GTM team. This is a high-impact, high-autonomy role. You'll own Perplexity's demand generation engine for our enterprise and business products, partnering closely with Sales, Product Marketing, and Revenue Operations to accelerate pipeline and revenue growth.
If you're the kind of marketer who builds their own tools, automates ruthlessly, and treats every campaign as an experiment-this role was written for you.
RESPONSIBILITES
- Own Perplexity's end-to-end demand generation strategy with direct accountability for enterprise top of funnel growth and downstream conversion to revenue.
- Architect and operate a modern demand engine using AI-native tooling-programmatic outbound, AI-personalized sequences, intent-based targeting, and automated workflows-that generates qualified pipeline at scale. We don't buy, we build.
- Design and execute multi-channel campaigns across paid, organic, ABM, events, partnerships, and emerging channels, continuously testing new motions, killing what doesn't work, and doubling down on incremental impact.
- Develop segmentation and targeting strategies for priority enterprise buyer personas, including IT leaders, executives, developers, and AI decision-makers.
- Partner with Product Marketing, Sales, and Revenue Operations to own and continuously improve the marketing-to-sales funnel.
WHAT WE'RE LOOKING FOR:
- 5+ years building and scaling multiple growth channels at a fast paced startup with a proven track record of revenue growth
- Experience and deep interest in building homegrown AI-driven outbound engines, programmatic personalization, and rapid experimentation platforms to scale yourself.
- Analytically rigorous: You are deeply data-driven, comfortable in SQL, attribution measurement, and BI tools like Looker, Omni, Hex, and Tableau. You build your own dashboards, define your own metrics, and make decisions based on evidence, not intuition.
- Thrives in ambiguity: You operate independently with urgency and ownership in fast-paced, early-stage environments where processes are still being defined.
