Member of Technical Staff (Software Engineer, Fraud Prevention)

Description

The fraud prevention team guards the company's products, users, and infrastructure against fraud and abuse at every stage: sign-up, authentication, payments, API usage, and product features.

The team builds and runs a real-time decisioning platform, along with the data pipelines for detection and model training, the integrations with product and payment systems, and the internal tools used for investigation and response.

As a software engineer, you take services from design through production operations and work alongside fraud analysts, ML engineers, and product teams. The aim is to make abuse costly for bad actors while keeping legitimate use smooth for everyone else.

Responsibilities

• Design, build, and run high-throughput backend services with low latency for fraud detection and prevention.
• Build data pipelines and real-time feature calculations that feed detections and ML models.
• Collect and process trust signals.
• Connect fraud decisions into product, authentication, and payment flows across the company.
• Keep production services reliable through monitoring, alerting, safe rollouts, and incident response.
• Build internal tools for investigation, enforcement, and audit trails.
• Work with fraud analysts to move newly observed abuse patterns into production detections quickly.

Requirements

• At least 5 years of building and operating high-throughput, latency-sensitive backend systems in production.
• Strong systems programming background. Experience with Rust, Go, or C++ is preferred, since the team writes Rust.
• Hands-on work with Kubernetes, Terraform, and cloud infrastructure.
• Solid grounding in data: stream and batch computation, and the trade-offs between caching and storage.
• A pragmatic, ownership-driven way of working: ship in small steps, measure results, and make failures degrade safely.
• Experience in fraud prevention, anti-abuse, or payments risk.
• Experience serving ML models in production.
• Client-side experience on web or mobile for collecting signals.