Staff Software Engineer, Payments and Applied Machine Learning

Stripe · Seattle, New York, San Franciscosenior

In short

▸Ingeniero de software principal enfocado en pagos e inteligencia artificial en Stripe.
▸Trabajas en todo el stack, definiendo estrategia técnica y estándares de calidad para sistemas críticos a gran escala.
▸Destaca la oportunidad de impactar en millones de transacciones y colaborar directamente con grandes empresas cliente.

Effective communication skills and a proven ability to work cross-team, cross-org, and cro

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What they ask for

✓10+ años de experiencia en ingeniería de software, con 5+ en roles de liderazgo técnico estratégico.
✓Experiencia liderando equipos en sistemas distribuidos, diseño de APIs y productos para usuarios.
✓Capacidad para impulsar proyectos a alto nivel y contribuir técnicamente cuando sea necesario.
✓Habilidades comprobadas para comunicarse y colaborar entre equipos, organizaciones y funciones.
✓Experiencia comprobada en soluciones prácticas que aceleren el crecimiento del negocio.
✓Capacidad para tomar decisiones técnicas en entornos ambiguos y con poca información.

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JavaRubyPythonTypeScriptKafkaFlyteAirflowMongoML systemsmodel serving

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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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