Full Stack Engineer, Growth

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. 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 products. Develop high-quality, robust backend APIs in Ruby that power responsive frontend experiences using React, JavaScript, and 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 with 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, with the ability to work across workstreams within your team and contribute to your peers' success Ability to thrive with a high level of autonomy and responsibility, and an entrepreneurial mindset Deep care for users' needs and the ability to be a steward of great user experiences Preferred qualifications Experience with machine learning, recommender systems, product-led growth, or lifecycle marketing Familiarity with basic analysis in large datasets (especially in systems like Redshift, Presto, or Trino) Experience incorporating observability into production systems and supporting their operation (on-call, incident response)