Head of Engineering (Adyen Protect)

Join Adyen, a leading global payment company, as the Head of Engineering for Adyen Protect. In this role, you will lead the development and scaling of our ML-first product suite designed to detect and mitigate payment fraud in real-time. You will be responsible for defining and executing the technical roadmap, scaling ML operations, ensuring engineering excellence, and advocating for our merchants. This is a unique opportunity for a visionary leader with a strong technical background and a passion for combating fraud in the fintech industry.

• Definir y ejecutar la hoja de ruta técnica para Adyen Protect, alineando las capacidades de Machine Learning con las necesidades del comercio electrónico global.
• Liderar equipos multidisciplinarios en la construcción y mantenimiento de infraestructura escalable para el entrenamiento de modelos, la puntuación en tiempo real y la experimentación automatizada.
• Establecer y mantener altos estándares de calidad y fiabilidad en la ingeniería, asegurando que nuestros sistemas de detección de fraude sean resilientes y capaces de procesar grandes volúmenes de datos.
• This is a role for a leader who thrives at the intersection of big data, predictive modeling, and high-availability systems
• Collaborative: You excel at building bridges between technical and non-technical stakeholders, explaining the "why" behind complex (ML) decisions
• Proven Leader: You have a track record of leading complex engineering organizations and managing other managers, specifically within high-growth fintech or SaaS environments
• Strategic Problem Solver: You can balance the immediate need for fraud mitigation with the long-term goal of reducing "false positives" to maximize merchant revenue
• Tech-Fluent: You remain technically literate and are comfortable diving into architecture discussions regarding distributed systems, data pipelines, and real-time processing
• ML & Data Enthusiast: You have a deep understanding of Machine Learning lifecycles, from data engineering and feature extraction to model deployment and monitoring
• Domain Expertise: Familiarity with fraud detection, risk management, or identity verification systems is highly preferred
• 5+ years of experience in manager-of-managers roles, overseeing multiple engineering teams
• 7+ years of technical experience, including significant tenure as a hands-on software or machine learning engineer
• Experience with High-Scale Systems: Proven track record of managing products that handle high-throughput, low-latency workloads (e.g., payments, cybersecurity, or real-time bidding)