Staff Software Engineer, Payments Intelligence
Stripe · On-site
MeritLog read this listing from Stripe's Greenhouse job board and last checked it on September 8, 2026.
Source: the employer's Greenhouse job board. Open the original listing for current details.
Job details
- Work model
- On-site
- Salary
- Not listed by source
- Location
- Seattle, New York, San Francisco
- Occupation
- Software Developers(O*NET 15-1252.00)
- Company website
- docs.google.com
Hiring context
How this role compares at Stripe
Stripe has 618 live roles in MeritLog’s catalog across 12 job families, and 153 of them are in engineering. 0 of those listings publish a pay range, a disclosure rate of 0%.
Stripe concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
What the role asks for
What you'd do
- Define technical strategy for multiple experiences across the Payment Intelligence portfolio, with a focus on quality and performance
- Champion a quality-first engineering culture - establish standards, tooling, and processes that make it easy to ship high-quality code at scale
- Partner with some of Stripe’s largest merchants to co-build the future of payment-centric intelligence
- Partner cross-functionally with product, design, and ML colleagues to ship the very best software possible
- Work across the stack - contributing to infrastructure and foundational systems, but also FE, API, and ML-adjacent work.
- 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role
- Experience leading engineering team(s) working on Distributed systems, API design, and user facing products
- Proven track record of delivering pragmatic solutions that accelerate business growth
- Ability to drive projects at a high-level while also being hands on and contributing directly to technical solutions as necessary
- Effective communication skills and a proven ability to work cross-team, cross-org, and cross-functionally.
What they're asking for
- Experience with payments systems and/or fraud detectionSkillPreferred
- Familiarity with ML systems in production: model serving, training pipelines, observability, and evaluationSkillPreferred
- Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorlySkillPreferred
- Experience across a range of software languages and frameworks; our stack includes Java, Ruby, Python, TypeScript, Kafka, Flyte, Airflow, and Mongo.SkillPreferred
- Experience navigating ambiguity in a fast-moving organization - you can make confident technical decisions with incomplete information and update gracefully when new constraints emergeSkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
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 Payment Intelligence is comprised of multiple product teams building AI-first solutions to some of our customers’ biggest challenges, including fraud/abuse (Radar), payment optimizations (AuthBoost), Disputes, Authentication, and merchant analytics. We’re a mix of machine engineering engineers and full-stack software engineers impacting ~every Stripe transaction, creating revenue opportunities for Stripe and our customers, and helping protect the broader ecosystem. We have the benefit and privilege of working on cutting edge technologies with incredible scale and reach while also working directly with our merchants every day to build the right products for their needs. What you'll do As a Staff Engineer on Payment Intelligence, you’ll work across our product portfolio to ensure we’re building in a consistent, efficient, and effective manner. Experience with large, distributed systems on the critical path will help candidates succeed, as will comfort working across the stack and interacting with ML teams and models. Responsibilities • Define technical strategy for multiple experiences across the Payment Intelligence portfolio, with a focus on quality and performance • Champion a quality-first engineering culture - establish standards, tooling, and processes that make it easy to ship high-quality code at scale • Partner with some of Stripe’s largest merchants to co-build the future of payment-centric intelligence • Partner cross-functionally with product, design, and ML colleagues to ship the very best software possible • Work across the stack - contributing to infrastructure and foundational systems, but also FE, API, and ML-adjacent work. Minimum requirements • 10+ years of software engineering experience, including 5+ years of experience in a strategic technical leadership role • Experience leading engineering team(s) working on Distributed systems, API design, and user facing products • Proven track record of delivering pragmatic solutions that accelerate business growth • Ability to drive projects at a high-level while also being hands on and contributing directly to technical solutions as necessary • Effective communication skills and a proven ability to work cross-team, cross-org, and cross-functionally. Preferred qualifications • Experience with payments systems and/or fraud detection • Familiarity with ML systems in production: model serving, training pipelines, observability, and evaluation • Prior experience with 0-1 product builds: you've started with a blank page and ended with a production system, and you have clear opinions about what makes that process go well or poorly • Experience across a range of software languages and frameworks; our stack includes Java, Ruby, Python, TypeScript, Kafka, Flyte, Airflow, and Mongo. • Experience navigating ambiguity in a fast-moving organization - you can make confident technical decisions with incomplete information and update gracefully when new constraints emerge
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