Staff Software Engineer, Payments Intelligence
Job description
About the role
Staff Software Engineer, Payments Intelligence
This role is central to how Payment Intelligence delivers value for Stripe customers. You will own the planning and execution for AI-first payment products. Your work spans Radar, AuthBoost, Disputes, Authentication, and merchant analytics. The goal is to elevate quality and reliability across large-scale systems.
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. The mission is to increase the GDP of the internet, and there is a significant amount of work ahead. This creates an opportunity to put the global economy within everyone's reach while doing the most important work of your career.
You will work alongside machine engineering experts and full-stack software engineers. This role impacts nearly every Stripe transaction, creating revenue opportunities for Stripe and our customers. It also helps protect the broader ecosystem. There is a benefit and privilege in working on cutting edge technologies with incredible scale while collaborating directly with merchants to build the right products.
About the Team
Payment Intelligence is comprised of multiple product teams. These teams build AI-first solutions to tackle some of the biggest challenges, including fraud and abuse, payment optimizations, disputes, authentication, and merchant analytics. The team is a mix of machine engineering engineers and full-stack software engineers. They impact nearly every Stripe transaction, creating revenue opportunities for Stripe and our customers, and helping protect the broader ecosystem.
The team works with cutting edge technologies that have immense scale and reach. There is daily interaction with merchants to ensure the products meet their needs.
What You'll Do
You will define technical strategy for multiple experiences within the Payment Intelligence portfolio. The focus is on quality and performance. You will champion a quality-first engineering culture. This involves establishing standards, tooling, and processes to ship high-quality code at scale.
Partnership is key. You will work with some of Stripe's largest merchants to co-build the future of payment-centric intelligence. Cross-functional collaboration with product, design, and machine learning colleagues is essential. You will contribute across the entire technology stack. This includes infrastructure, foundational systems, frontend, API, and ML-adjacent work.
Specific responsibilities include designing data platforms that power fraud prevention and monetization logic. You will translate complex merchant needs into resilient product flows that scale globally. The role requires championing testing and deployment practices that keep releases safe and fast.
Key Facts
Location options include Seattle, New York, and San Francisco. The engagement is full-time. The compensation range is $190,000 to $340,000 USD per year.
Requirements
You must bring 10+ years of software engineering experience. This should include 5+ years in strategic technical leadership roles. Experience leading engineering teams is essential. You must have a proven track record of delivering pragmatic solutions that accelerate business growth.
The ability to drive projects at a high-level while remaining hands-on is required. Clear communication skills are necessary for effective cross-team, cross-organizational, and cross-functional collaboration. Experience with large, distributed systems on the critical path is a key factor for success. Comfort working across the stack and interacting with ML teams and models is expected.
Preferred Qualifications
A background in payments systems and/or fraud detection is valuable. Familiarity with ML systems in production is beneficial. This includes model serving, training pipelines, observability, and evaluation.
A record of shipping greenfield products from concept to production is a strong asset. You have started with a blank page and ended with a production system, with clear opinions on what makes that process successful.
Skills & Tools
The stack includes a wide range of software languages and frameworks. You will work with Java, Ruby, Python, TypeScript, Kafka, Flyte, Airflow, and Mongo. Experience navigating ambiguity in a fast-moving organization is critical. You can make confident technical decisions with incomplete information and update gracefully when new constraints emerge.