Software Engineer, Fraud

Recruiting From Scratch•San Francisco, CA

16h•Onsite

About The Position

This high-growth AI company is building the infrastructure that powers how human expertise is leveraged to train and improve frontier AI systems. With a large global network and partnerships with leading AI labs and enterprises, the platform operates at massive scale, enabling real-world workflows that directly shape the future of AI. Backed by top-tier investors and operating profitably, the company is entering its next phase of growth, focused on reliability, trust, and platform integrity.

Requirements

4+ years of experience building production backend systems
Strong engineering fundamentals with experience in scalable system design and data-driven applications
Ability to identify patterns in complex systems and translate them into technical solutions
High ownership mindset with comfort operating in fast-moving, ambiguous environments
Strong judgment in balancing risk, speed, and user experience

Nice To Haves

Experience working on fraud detection, abuse prevention, or trust & safety systems
Prior experience building fraud, risk, or trust & safety systems at scale
Familiarity with identity verification, anomaly detection, or behavioral analytics
Experience working with large datasets, event streams, or real-time detection systems
Background in high-growth startups or environments with rapid iteration cycles

Responsibilities

Design and build fraud detection and prevention systems across key surfaces, including identity verification and platform abuse
Identify fraud patterns and translate them into scalable backend systems, tools, and workflows
Partner closely with product and engineering to define fraud strategy and prioritize high-impact initiatives
Develop systems that detect suspicious behavior, mitigate risk, and reduce fraudulent activity in real time
Improve visibility into fraud trends, risk exposure, and system effectiveness through monitoring and analytics
Operate autonomously in ambiguous environments, owning large problem areas end-to-end
Balance security, user experience, and operational efficiency when designing fraud prevention systems