The role
- COMP
- $240K - $320K
- EQUITY
- Highly Competative Equity
- LOCATION
- San Francisco · New York · Canada
- WORKPLACE
- On-site or Remote
- EXPERIENCE
- 4+ years
- VISA
- None, Visa transfers
- STACK
- Figma, Salesforce
- INDUSTRY
- B2B, Data, Marketing, AI, Enterprise
/roles — ROLE_298
Product Lead, AI Personalization
Late-stage marketing data platform expanding into AI agents that personalize websites and mobile apps
The company
A late-stage data and AI company whose platform lets businesses activate customer data from their own warehouse for marketing, advertising, and personalization, increasingly through AI agents.
- STAGE
- scale-up
- FUNDING
- $320M+ raised
- TEAM
- 350+ people
- FOUNDED
- 2018
- BACKING
- backed by Y Combinator, Goldman Sachs
JD — the work
About the role
This is the founding product role for the company's newest and largest bet: AI agents that personalize what customers see inside websites and mobile apps. It sits next to existing agent products for paid advertising and lifecycle messaging and reuses the same agents and customer data layer, but it sells to a new audience, the people who own product and growth, and depends on live experimentation plus delivery through the browser and at the edge. You would own what gets built, in what order, and how it goes to market, with high visibility to the founders and leadership.
What you'll do
- Interview enterprise growth and product leaders in depth about how they currently tailor their websites and apps
- Translate what you learn into a roadmap anchored to clear revenue goals
- Decide which actions agents take on their own, such as segments, variants, and traffic allocation, and which need human sign-off
- Create the review cycle through which customers come to trust agent decisions over time
- Share ownership of pipeline, sit in on sales calls, sharpen competitive positioning, and build rollout playbooks with customer success
What they're looking for
- 4+ years in product and a record of taking products from zero to real revenue, preferably in B2B SaaS
- Technical depth to debate architecture tradeoffs with senior engineers, such as batch versus real-time or caching
- Commercial instinct: you think about conversion, expansion, and pipeline and tie roadmaps to revenue
- Speed and comfort on a small, autonomous team that uses AI heavily in its own work
- Ability to earn trust across engineering, design, sales, customer success, and leadership