Perplexity
Member of Technical Staff (Software Engineer, Fraud Prevention)
London, GB
Role snapshot
Perplexity is hiring a Member of Technical Staff (Software Engineer, Fraud Prevention) on a full-time basis. This is a remote role open to candidates in GB. The listing highlights Search.
- Company
- Perplexity
- Location
- London, GB
- Work mode
- Remote
- Job type
- Full-time
- Posted
- Oct 23, 2026
Who this role suits
The listing does not state a required experience level here. Read the requirements in the description below and apply if they match your background.
How to prepare your application
- Check your résumé against the listed skills (Search) and give each one a concrete example: what you built or achieved, not just that you used it.
- Match your résumé to the requirements in the description, using the same wording where it is honest to do so.
- Prepare a short example for each requirement you meet, and be ready to explain any you only partly meet.
- Read what Perplexity publishes about its product or team, so you can say clearly why this role and this company.
- For remote roles, show that you communicate clearly in writing and can work without close supervision.
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About the role
About the role
Perplexity's fraud prevention team protects our products, users, and infrastructure from fraud and abuse across the whole lifecycle: sign-up, authentication, payments, API usage, and product features. We build and operate a real-time decisioning platform together with the surrounding systems: data pipelines for detection and model training, integrations with product and payment systems, and internal tooling for investigation and response. As a software engineer on the team, you will own services end to end, from design to production operations, and work closely with fraud analysts, ML engineers, and product teams to make abuse expensive and legitimate usage frictionless.
Responsibilities
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
Qualifications
5+ years building and operating high-throughput, latency-sensitive backend systems in production
Strong systems programming skills; Rust, Go, or C++ experience preferred (we write Rust)
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
Fraud prevention, anti-abuse, or payments-risk domain experience
Experience serving ML models in production
Client-side experience (web or mobile) for signal collection