Join our cross-functional fraud detection squad where you'll build systems that protect millions of customers while keeping the good ones flowing seamlessly through our platform.
In this role you'll:
Build fraud detection systems using microservices in Typescript (NestJS) and Ruby on Rails, running over Kubernetes to catch bad actors while keeping legitimate customers happy
Leverage our autonomous tools to manage development flow-from environment setup to production deployment-so you spend time solving fraud, not fighting infrastructure
Collaborate with data scientists, product managers, and fraud analysts in a self-sufficient squad to hit aggressive fraud prevention OKRs
Own your domain's code quality, performance, and scalability as fraudsters get smarter and transaction volumes explode
Design systems that make split-second decisions on claims and applications, balancing security with customer experience
Coach and mentor other engineers while staying ahead of evolving fraud patterns and attack vectors
Partner with our AI/ML teams to implement and optimize machine learning models that detect fraud in real-time
Requirements: 6+ years as a backend engineer, ideally with experience in fraud detection, risk management, or high-stakes decision systems
BSc in Computer Science, Mathematics, or equivalent experience
Passionate about technology and the cat-and-mouse game of fraud prevention
Broad knowledge of modern backend frameworks, tools, and architecture-especially real-time processing and decision engines
Experience with high-scale, production-grade projects where uptime and accuracy are non-negotiale
Past contributions to open source projects (bonus points for security or fraud-related work)
Ability to work in an office environment a minimum of 3 days a week
Enthusiasm about learning and adapting to the exciting world of AI-a commitment to exploring this field is a fundamental part of our culture
This position is open to all candidates.