Backend Engineer - North America Risk Prevention

Description

The team is North America Risk Prevention, a core group at the company focused on its largest and fastest-moving market, North America.

The team protects customers and the business from financial crime. It processes billions in volume through risk and fraud prevention systems that must keep pace with customers.

The team runs machine learning risk assessments in real time each time a customer uses the calculator to quote a transaction.

It owns the risk infrastructure for Instant ACH, a high-value US feature that delivers instant transfers even though the payment network does not support them.

Software engineers, data analysts and data scientists work together daily on rules, ML models and support for the chargeback and fraud investigation teams.

Fraud is the current focus. The scope is growing to cover Sanctions and AML (Anti-Money Laundering) risk in the US and Canada.

The company is a global technology business that builds ways to move and manage money internationally.

Responsibilities

• Design and build rules and risk checks that stop fraud losses while keeping the experience smooth for legitimate customers.
• Learn the specific fraud patterns you are guarding against and measure how your code prevents losses.
• Put models from data scientists into production and work with data analysts to refine rule sets.
• Raise the automation level of the platform so it can handle new risk types in the US and Canada, including Sanctions screening, AML (Anti-Money Laundering) and other controls.
• Own what you build, including running it in production and keeping real-time monitoring robust and reliable for North America.
• Build strong working relationships with the wider engineering team and US stakeholders, and understand the reasoning behind each feature.

Requirements

• 4+ years of experience with Java, Kotlin or another JVM language, with deep knowledge of Spring.
• Ability to design solutions that handle high throughput and low latency, keeping p99 end-to-end latency under 1 second for real-time risk and fraud checks at very high volume.
• Deep understanding of JDBC, database internals and query optimization.
• Hands-on experience with Kafka, Kafka Streams or Apache Flink for real-time event processing.
• Experience with CI/CD pipelines and building scalable, resilient distributed systems.
• Customer focus: you use data to fix pain points such as false positives, and you care about user experience, since risk checks run every time a user uses the calculator.
• Full ownership of projects, from the first idea through to monitoring in production.
• Ability to explain complex technical concepts to non-technical audiences.
• Comfortable working daily with data scientists to put models into production and with data analysts to refine rule sets.
• Even better if you have:
• ML basics: data pipelines, feature engineering and precision/recall, since models are deployed for Instant ACH and transaction monitoring.
• Experience with OLAP databases or data lakes such as Apache Iceberg, including Kafka ingestion.

Conditions

The team is spread across Budapest and Austin.

You will work closely with US-based colleagues to understand the North American market and customer needs.

Occasional travel to the US for in-person collaboration.

The company is committed to diverse, equitable and inclusive teams.