Product Design Lead, AI Growth

Rippling•Seattle, WA

1d•$174,000 - $290,000•Onsite

About The Position

As the design lead for Growth, you'll shape how customers adopt AI across Rippling and come to depend on it. Thousands of companies already run HR, IT, and Finance on Rippling. The job is getting the admins and employees inside them to trust AI with real work. Rippling is in a unique position to change how companies run with AI because it already holds so much of the company: who works there, what they're paid, which laptops and apps they use, and who approves what. AI with that context can take on actual operational work. Customers still have to choose to use it, though, and the growth patterns you design are how that happens. An admin tries something small, sees it work on their own company's data, and gives Rippling AI a bigger job next time. You will help customers see Rippling's idea of the future of work. Designers at Rippling are product builders. You'll work with PMs, engineers, and data scientists to define problems and ship experiences that change customer behavior. The work here starts in LLMs to clarify thinking, moves into tools like Cursor and Claude Code for refinement, then ships to customers. You'll stay involved through testing and launch, and own the outcome with your partners. If you've moved real numbers without cheapening the product, we want to talk to you.

Requirements

8+ years of end-to-end product design experience shipping complex, high-impact products from concept to launch.
A portfolio of shipped work that measurably changed behavior, such as activation, adoption, retention, or conversion. Show us the experiments that lost, too, and what you did next.
Experience setting growth direction for a whole product area and getting teams you don't manage to follow it.
Hands-on growth design across onboarding, activation, and monetization. B2B or AI products are a plus, especially where the buyer and the daily user are different people.
Comfort with funnels, cohorts, and experiment design, and the judgment to spot a result that's misleading.
Daily use of LLMs and AI prototyping tools (Claude, ChatGPT, Cursor, Claude Code, or similar), whether or not you write production code.
Strong interaction and visual craft. Growth surfaces are often the first thing a customer sees.
Clear communication, including explaining a test result to people who were hoping for a different one.

Responsibilities

Drive design for AI adoption across Rippling, from an admin's first setup to an employee's daily use.
Work with PM and data science to define what an activated AI user looks like, and the guardrail metrics that tell you when a win is hurting retention.
Build shared growth patterns (entry points, prompt suggestions, setup flows, upgrade moments) so product teams stop building their own.
Run experiments with your PM and data partners. Read results with judgment, and flag the ones that win on the metric and lose with the user.
Design upgrade and usage-limit moments that feel fair and never come as a surprise.
Spend time with customers to see where AI helps them and where they give up on it. Turn that into priorities for the domain.
Use LLMs to sharpen problems and requirements, and prototype in code with AI tools so you're testing real interactions.
Raise the bar for growth design across the org. Share what you learn, including from failed tests, and coach designers who are newer to growth.