Synced from Greenhouse · Oct 20

Staff Software Engineer, Radar

StripeSan Francisco, SeattlePosted Oct 20, 2026
Software EngineerStaff
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Mirrored from Stripe's own Greenhouse careers system · refreshed hourly

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Oct 20
Posted
Greenhouse
Applicant system
Job descriptionReq 8287912

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

Radar helps businesses prevent payments fraud and abuse while enabling legitimate customers to transact with confidence. We combine machine learning and AI with the intelligence of Stripe’s global network to make sophisticated fraud prevention accessible to businesses of all sizes.

Our work spans payments fraud detection, protection against abuse beyond the payment, enterprise APIs that bring Radar’s capabilities into businesses’ own systems and payment flows, and the platform that powers it all. We build everything from reliable, low-latency infrastructure to intuitive tools that help users understand threats and control how they respond.

Fraud evolves constantly, and so do we. We work directly with users to understand emerging attacks, turn advances in ML and AI into effective defenses, and build products that protect and grow their revenue.

What you’ll do

As a software engineer on Radar, you’ll build products and infrastructure that help businesses understand and stop fraud and abuse. Your work will span backend services, enterprise APIs, and user experiences that put sophisticated prevention capabilities into our customers’ hands.

You’ll own problems from investigation through launch, partnering with  product managers, designers, and data scientists. You’ll have opportunities to scale systems that make real-time decisions across Stripe’s global payments network, bring advances in ML and AI into production, and build new products from scratch. Every improvement can have a direct impact on the revenue our users retain and the legitimate customers they serve.

Responsibilities

  • Build and operate reliable, low-latency services that detect and prevent fraud and abuse at scale
  • Design APIs and dashboard experiences that help businesses investigate threats, configure defenses, and understand how Radar protects them
  • Develop the shared platform and infrastructure that enable teams to build and launch new Radar capabilities
  • Work directly with users to understand emerging threats and turn those insights into broadly useful products
  • Partner with ML engineers and data scientists to bring new signals, models, and AI capabilities into production
  • Own projects end to end, from technical design and implementation through rollout, measurement, and iteration
  • Uphold a high bar for engineering quality, reliability, and product craft while moving quickly as threats evolve

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

  • 10+ years of backend and/or full-stack software development experience, with a track record of owning large, ambiguous systems end-to-end.
  • Strong coding skills in any programming language, with experience building and maintaining production software
  • Demonstrated technical experience leading the design and delivery of large, complex software projects from early definition through production launch.
  • Experience leading and unblocking a group of engineers on a substantial project as a senior individual contributor.
  • Significant hands-on coding as a senior IC leader in the last year. 
  • Ability to work across systems and technologies, learn unfamiliar codebases, and make thoughtful technical trade-offs
  • Ability to operate effectively in high-ambiguity environments: framing problems, making durable technical decisions, and creating an actionable path forward.
  • Excellent cross-functional and cross-organizational collaboration skills, with the ability to align teams with different systems, priorities, and constraints.
  • Understanding of basic data science concepts, like linear models, precision, recall, and more
  • Experience building consumer products at scale, particularly products that require a high degree of user trust.
  • Experience working closely with fast customers, including leading upsell calls

Preferred qualifications

  • Track record of working closely with data science and ML teams to ship products to users
  • Experience working on 0→1 products or taking new capabilities from concept through launch and iteration.
  • Experience with Java, Ruby, and/or TypeScript. We care more about strong engineering fundamentals and the ability to learn than expertise in a particular language or framework.
  • Experience building payments, money-movement, fintech, or other regulated financial products.
  • Experience building consumer products at scale, particularly products that require a high degree of user trust.
  • Familiarity with stablecoins, digital assets, or the infrastructure that enables global financial products.

 

View original posting on Greenhouse

What applying to Stripe usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Stripe can typically expect an initial application review followed by a recruiter screen, assuming the profile aligns with the role's requirements. The process may include multiple stages, such as hiring manager conversations, technical or role-specific assessments, and panel interviews covering relevant skills and competencies. Greenhouse-based processes commonly allow candidates to track application status through an online portal and may involve structured interview scorecards used internally for evaluation consistency. Communication is often handled via email, and response times vary depending on team needs, role seniority, and overall hiring volume. Candidates can generally expect some degree of transparency about next steps, though specific timelines and the number of interview rounds are not guaranteed and may differ by department or position.

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