Staff Java Engineer - Merchant Fraud Prevention
Adyen
Staff Java Engineer - Merchant Fraud Prevention
Adyen is seeking a Staff Java Engineer for its Merchant Fraud Prevention group in Amsterdam. The role involves defining the long-term technical vision across 2-3 engineering teams, architecting high-throughput distributed systems, and partnering with Data Science, ML Engineering, and Fraud Operations. Candidates need deep distributed systems expertise, ML systems experience, and a track record of technical leadership.
Staff Java Engineer - Merchant Fraud Prevention
Adyen is seeking a Staff Java Engineer for its Merchant Fraud Prevention group in Amsterdam. The role involves defining the long-term technical vision across 2-3 engineering teams, architecting high-throughput distributed systems, and partnering with Data Science, ML Engineering, and Fraud Operations. Candidates need deep distributed systems expertise, ML systems experience, and a track record of technical leadership.
Salary
Core Qualifications
Technical (Must-have)
Soft Skills
Preferred Qualifications
Technical (Nice-to-have)
Key Responsibilities
- Own the multi-year technical north star vision for the group, together with the technical leads of each team in the group
- Design and evolve high-throughput, low-latency distributed systems capable of processing real-time merchant transactions, integrating complex machine learning models, and handling massive big data pipelines
- Partner closely with the Director of Engineering to assess organizational health, surface systemic engineering bottlenecks, and align long-term technical investments with Merchant protection goals
- Shape the strategic roadmap alongside the Director of Engineering, fellow Staff Engineers, and Product leadership
- Establish consistent architectural patterns, engineering practices, and quality bars across 3 fraud-focused teams
- Bring clarity to ambiguity as new fraud vectors and product requirements emerge
- Sponsor and mentor senior engineers, build clear growth paths, model high engineering standards, and foster a culture of engineering excellence and psychological safety
- Partner with Data Science and ML Engineering so infrastructure supports fast model deployment, feature stores, and real-time inference, without compromising latency or reliability
- Work closely with Fraud Operations to translate emerging fraud patterns and investigative findings into platform and tooling requirements
- Ensure engineering systems give Fraud Ops the visibility, control, and response speed they need to act on evolving threats