Senior Product Managerניהול

About the Role:

We are looking for a Senior Product Manager to join our Detection team and help drive our detection-based solutions. In this role, you will own a core part of the platform that detects and decides, in real time, whether an interaction can be trusted — telling humans from agents from fraudsters in real time, at a moment when that line is blurring fast. Fraud and risk now touch every interaction, and autonomous AI agents are dissolving the old assumptions about what "human," "trusted," and "normal" even mean. You'll fuse device, behavioral, network, and contextual signals into accurate risk real-time decisions across login, transactions, and the full user journey - and help invent the detection approaches this new landscape demands, not just tune the ones that worked yesterday.

This is a balanced role at the intersection of deep detection technology and real customer outcomes. You'll translate identity fraud and risk problems into a clear roadmap, work shoulder-to-shoulder with researchers, data scientists and engineers on detection quality, and make sure what we ship moves the needle for customers. Staying ahead of this threat landscape — from classic fraud and bots to increasingly sophisticated automated and agent-driven attacks — is central to the job. You won't need to be a data scientist, but you should be genuinely curious about how detection works and comfortable reasoning about precision, recall, and false positives with the team.

What you’ll do:

Own the roadmap for your area of the detection platform — from discovery and problem definition through delivery and adoption — and align it with company strategy and customer needs.

Partner closely with data science and engineering to improve detection quality: recommendation accuracy, coverage of new fraud and abuse patterns, model and rule performance, and reduction of false positives.

Define what "good" looks like and track the metrics that matter — detection rate, false-positive rate, customer impact, latency, and adoption — and use them to drive decisions.

Engage regularly with customers, TAMs, and analysts to understand real fraud problems and the operational reality of running detection at scale.

Anticipate emerging threats, including automated and AI-driven abuse, and shape how the platform detects and responds to them.

Write clear, lean specs and PRDs, and make sharp scoping calls that get value to customers quickly without over-building.