Member of Technical Staff (Software Engineer, Fraud Prevention)

The role

You will design, build, and operate high-throughput, low-latency backend services for fraud detection and prevention. You will work on data pipelines, real-time feature computation, and internal tooling to protect products, users, and infrastructure.

What you will do

• Design, build, and operate high-throughput, low-latency backend services for fraud detection and prevention
• Build data pipelines and real-time feature computation that power detections and ML models
• Collect and process trust signals
• Integrate fraud decisions into product, auth, and payment flows across Perplexity
• Own reliability of production services: observability, alerting, safe rollouts, incident response
• Build internal tooling for investigation, enforcement, and auditability
• Partner with fraud analysts to turn new abuse patterns into production detections quickly

Required qualifications

• 5+ years building and operating high-throughput, latency-sensitive backend systems in production
• Strong systems programming skills
• Hands-on experience with Kubernetes, Terraform and cloud infrastructure
• Solid data fundamentals: stream/batch computations, caching and storage trade-offs
• Pragmatic, ownership-driven approach: ship incrementally, measure, and make failures degrade safely

Nice to have

• Rust, Go, or C++ experience preferred (we write Rust)
• Fraud prevention, anti-abuse, or payments-risk domain experience
• Experience serving ML models in production
• Client-side experience (web or mobile) for signal collection

About the company

Perplexity's fraud prevention team protects products, users, and infrastructure from fraud and abuse across the whole lifecycle.