Full Stack Engineer, Builder Experience

Stripe; United States; Remote; USD 120,000 - 150,000; Full time

Job summary

Stripe is seeking product-minded engineers to rethink how products are built, not just digitize existing processes. You’ll identify high-friction parts of Stripe’s product-development lifecycle and prototype bold new approaches.

This hands-on role spans the stack, combining traditional software engineering with emerging AI capabilities, and requires navigating ambiguous problem spaces to discover the right product, interface, and architecture.

Responsibilities

• Design and build tools that help Stripe teams shape better products, ship with greater speed and confidence, and learn from users more quickly.
• Develop AI-native workflows and agents that synthesize context, automate repetitive work, surface risks, and help builders make better decisions.
• Own projects end to end: identify high-value problems, develop prototypes, test them with users, measure their impact, and scale the approaches that work.
• Work across backend systems, data sources, internal platforms, and AI capabilities to deliver integrated solutions.

Job description

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

The Builder Experience Team makes it easier for Stripe’s product teams to build the right products, ship them with confidence, and help users realize value from them.

In order to build a great product, product teams must develop a deep understanding of users, shape and test ideas, coordinate across functions, navigate launch requirements, identify risks, gather feedback, and manage products after launch.

Today, many of these workflows are fragmented, manual, or built around processes and tools that predate recent advances in AI.

We are a small, AI-native team reimagining how Stripe builds, ships, and ramps products. We experiment with new approaches across AI agents, automation, and process—and scale the ones that work. Our initial areas of focus include reinventing launch readiness from gates into guidelines, giving product teams richer and more timely context, and shortening the feedback loops between builders, users, Sales, and Support.

Our users are Stripe’s product managers, engineers, designers, researchers – and we help to simplify the interactions with the cross-functional teams that help bring products to market. We work closely with teams including all of our business unit PMs, Product Operations, and Kai, Stripe’s internal AI platform.

What you'll do

We’re looking for product-minded engineers who want to rethink how products get built—not simply digitize existing processes. You’ll identify high-friction parts of Stripe’s product-development lifecycle, rapidly prototype new approaches, put them in the hands of real teams, and turn the strongest experiments into scaled solutions used by every product team at Stripe.

This is a hands-on role with broad product and technical scope. You’ll work across the stack, combining traditional software engineering with emerging AI capabilities. You’ll operate in ambiguous problem spaces where the right product, interface, and technical architecture must be discovered together.

You will:

• Design and build tools that help Stripe teams shape better products, ship with greater speed and confidence, and learn from users more quickly.
• Develop AI-native workflows and agents that synthesize context, automate repetitive work, surface risks, and help builders make better decisions.
• Own projects end to end: identify high-value problems, develop prototypes, test them with users, measure their impact, and scale the approaches that work.
• Work across backend systems, data sources, internal p