Staff Software Engineer, Payment Systems

Stripe · FinTech · Banque & Paiement · Seattle, New York, San Francisco

Seattle, New York, San FranciscoIngénierie10 septembre 2026Lu sur Greenhouse
Sur siteStaff / Principal

Fraîcheur de l'offre

En ligneVérifiée chez l'éditeur il y a 5 h

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  • En ligne depuis 9 j
  • Stripe retire ses offres au bout de 7 j en médiane (73 offres closes observées)

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Ce que dit l'annonce

Define technical strategy for Payment Intelligence product portfolio, champion engineering quality standards, and partner with merchants on payment-centric intelligence solutions.

  • 10+ ans d'expérience
  • Contributeur individuel

Lu dans le texte de l'annonce par un modèle de langage le 14 septembre 2026 — indicatif, vérifiez sur l'annonce d'origine.

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

Stack repérée

En bref

Publiée le 10 septembre 2026 · vue pour la première fois le 6 septembre 2026

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