Staff Software Engineer, Payment Systems

at Stripe
USD 224,000-336,000 per year
SENIOR
✅ On-site

Tech Stack

AI API @ 4 Airflow @ 6 Communication @ 6 Distributed Systems @ 4 Fraud @ 4 Java @ 6 Kafka @ 6 Leadership @ 8 Machine Learning @ 3 MongoDB @ 6 Observability @ 3 Payments Python @ 6 Ruby @ 6 Technical Leadership @ 8 TypeScript @ 6

Details

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. Stripe's mission is to increase the GDP of the internet.

About the Team

Payment Intelligence comprises multiple product teams building AI-first solutions for fraud and abuse, payment optimization, disputes, authentication, and merchant analytics. The team includes machine learning engineers and full-stack software engineers working at the scale of nearly every Stripe transaction.

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 by establishing 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.
  • Collaborate cross-functionally with product, design, and machine learning colleagues to ship high-quality software.
  • Work across the stack, contributing to infrastructure and foundational systems as well as front-end, API, and machine-learning-adjacent projects.

Requirements

  • 10+ years of software engineering experience, including 5+ years in a strategic technical leadership role.
  • Experience leading engineering teams working on distributed systems, API design, and user-facing products.
  • A proven track record of delivering pragmatic solutions that accelerate business growth.
  • Ability to drive projects at a high level while remaining hands-on and contributing directly to technical solutions when necessary.
  • Effective communication skills and a proven ability to work across teams, organizations, and functions.

Preferred Qualifications

  • Experience with payment systems and/or fraud detection.
  • Familiarity with machine learning systems in production, including model serving, training pipelines, observability, and evaluation.
  • Prior experience building products from 0 to 1, from an initial concept through production deployment.
  • Experience with a range of software languages and frameworks. The stack includes Java, Ruby, Python, TypeScript, Kafka, Flyte, Airflow, and MongoDB.
  • Experience navigating ambiguity in a fast-moving organization, making confident technical decisions with incomplete information and adapting when constraints change.

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