Product Lead, Agentic Personalization

Hightouch is the modern AI platform for marketing and growth teams. Our AI agents reimagine marketing workflows, allowing marketers to create content, plan campaigns, and execute strategies with transformational velocity and performance.

Hightouch is a rare company built on the intersection of two fundamental technological shifts: advances in LLMs and agentic AI, and the creation and rapid adoption of cloud data warehouses like Snowflake and Databricks. Building on these tailwinds, we’ve become a leader in AI marketing and partner with industry leaders like Domino’s, Chime, Spotify, Ramp, Whoop, Grammarly, and over 1000 others.

Our team focuses on making a meaningful impact for our customers. We approach challenges with first-principles thinking, move quickly and efficiently, and treat each other with compassion and kindness. We look for team members who are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals.

When you open Spotify, the homepage is different for every user. When you browse Nike's site, products are ranked by what Nike thinks you'll buy. When you log into Chase, offers are tailored to your spending. This is web and mobile personalization: deciding in real time what each customer sees inside your product. It directly moves conversion, retention, and revenue at the point where customers are already engaged.

Almost nobody does it well outside of companies that build it from scratch. A single experiment (testing whether high-spend users convert better seeing a loyalty upsell on the account page) requires an analyst to build the segment, a PM to write targeting rules, a designer to create variants, an engineer to instrument the test, and someone to monitor results. Most teams run 5–10 per quarter and end up with a handful of static rules covering a fraction of their users.

The tools that exist (Optimizely, Dynamic Yield, Adobe Target) handle infrastructure but don't solve the coordination problem. Every experiment, audience, and piece of content still requires manual configuration. They also force companies to duplicate customer data into a proprietary store, adding months of implementation and permanent vendor lock-in.

The shift from "AI assists a step" to "AI owns a workflow" is already happening in software engineering. Personalization is ready for the same shift.