Engineering Manager, Fraud
Engineering · Full-time · San Francisco
ApplyOur mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.
About the role
We’re hiring an Engineering Manager, Fraud & Abuse to build the systems that protect Cursor from fraud, abuse, and misuse as we scale.
This is a hands-on role: you will set direction, write code, and build the platform, tooling, and decisioning systems we use to detect, prevent, and respond to fraud and abuse.
You will work cross-functionality to understand our current risks and workflows across the company. This role is specifically about mitigating known vectors while building strong defenses that are accurate, scalable, and practical to operate.
What you’ll do
Improve fraud and abuse systems end-to-end, from detection and risk scoring to enforcement and reporting. Enhancing existing fraud prevention systems provided by vendors.
Write and ship code directly in the codebase, unblock critical work, and set a high bar for engineering quality, reliability, and execution. This will involve making product enhancements to assist with mitigating fraud.
Build tooling and guidance that operations teams will use handle high-risk accounts.
Hire and grow the team by recruiting, interviewing, closing, and onboarding engineers, and by establishing strong operating rhythms and engineering standards.
Design and ship a centralized platform that incrementally delivers value to known fraud then scales as vectors diversify and our product evolves.
Partner deeply with Billing, Growth, Finance, Security, Operations, and Legal to identify major fraud and abuse risks, improve signal quality, and build defenses that are effective without creating unnecessary friction or complexity.
Own outcomes such as fraud loss, detection latency, enforcement quality, and investigation time.
You may be a fit if
You have built fraud detection and abuse prevention for usage-based services in the past.
You have implemented risk scoring, policy engines, enforcement pipelines, case management, payments or subscriptions systems, and human-in-the-loop review workflows.
You have experience mitigating social engineering attempts.
You’ve leveraged Stripe, WorkOS, and other third-party vendors creatively with success.
You have experience working cross-functionally with non-engineering teams.
You have led incident response for fraud/abuse incidents.
You are excited and capable to be hands-on writing and debugging Typescript on day 1.
You have significant experience managing and developing engineering teams, including hiring and performance coaching.
You have experience in LLM Safety & Integrity.