Full Stack Engineer, Growth

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

Our Growth team is on a mission to acquire, convert and grow millions of merchants globally across Stripe's full suite of financial products. We are a cross functional team of engineers, scientists, marketers, designers and product managers that deliver the insights, algorithms, internal systems and tools, and user-facing experiences that fuel Stripe's growth. We make it easy for businesses around the world to find Stripe, get started, and grow.

As part of the Growth Engineering team, you will build the systems, products, internal tools, and customer-facing experiences that power intelligence behind our go-to-market and product-led growth. This includes building ML powered recommendations and growth experimentation engines, multi-channel notifications systems, and key growth-related customer experiences (e.g., onboarding flows, user dashboards, product recommendations).

What you’ll do

As a Full Stack Engineer on the Growth team, you'll build and ship experiments and product improvements across stripe.com and the Dashboard to help businesses find and get started on Stripe. You'll work on critical parts of the funnel for self-serve users, ensuring their experience on Stripe is consistently high quality and useful. With other engineers and data scientists, you'll turn ML-powered recommendations, messaging, and experimentation into impact that moves company metrics.

Responsibilities 

• Build and maintain scalable systems and customer experiences that help businesses discover, onboard, and grow with Stripe's products
• Develop high-quality, robust backend APIs in Ruby that power responsive frontend experiences using React/JavaScript/CSS
• Implement and iterate on ML-driven recommendations, experimentation frameworks, and growth optimization features
• Work with data scientists and product managers to translate growth hypotheses into technical implementations and A/B tests
• Contribute to shared platforms and tools that enable rapid experimentation across growth initiatives
• Debug production issues across the full stack and participate in on-call rotations
• Write maintainable, well-tested code that follows team conventions and best practices

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 2-5 years of industry software engineering experience
• Strong coding skills in any programming language (we understand new languages can be learned on the job so our interview process is language agnostic)
• Experience delivering small projects independently and contributing to medium projects with guidance
• Strong collaboration skills, can work across workstreams within your team and contribute to your peers' success
• Have the ability to thrive on a high level of autonomy, responsibility, and think of yourself as entrepreneurial
• Interest in working as a generalist across varying technologies and stacks to solve problems and delight both internal and external users
• Experience building, maintaining, and running production services and backend APIs
• Deep care for users' needs, and ability to be a steward of crafting great experiences

Preferred qualifications

• Experience with machine learning, recommender systems, product-led growth, and/or lifecycle marketing
• Familiarity with basic analysis in large datasets (especially in systems like Redshift or Presto/Trino)
• Experience incorporating observability into production systems and supporting their operation (oncall, incident response)