
Head of Engineering - Risk & Financial Crime
- Amsterdam, Noord-Holland
- Vast
- Voltijds
- Lead and mentor multiple multidisciplinary engineering teams in Amsterdam focused on data-driven risk and financial crime products.
- Drive the technical strategy and execution for building scalable and resilient systems for financial crime detection and mitigation, covering the entire business lifecycle on the platform.
- Oversee the development and deployment of machine learning models and data pipelines for real-time and batch risk assessment.
- Explore and implement applications of cutting-edge AI technologies, including GenAI and LLMs, to automate manual investigation tasks, improve detection accuracy, and provide rich context for human reviewers and models.
- Collaborate closely with expert investigators and operations teams to understand their workflows, integrate human feedback into automated systems, and ensure tools meet their needs.
- Partner with product managers, data scientists, and other engineering teams globally to define product requirements, prioritize initiatives, and integrate risk capabilities into Adyen's platform.
- Ensure systems are built with robust monitoring, explainability, and governance frameworks to meet regulatory requirements and maintain high quality and fairness.
- Stay informed about the latest advancements in financial crime typologies, risk management techniques, and AI/ML technologies, applying relevant insights to Adyen's products.
- Proven experience leading and mentoring multiple engineering teams, fostering a collaborative and high-performing environment.
- Significant experience in building and deploying data-driven products and systems at scale, ideally in a domain involving risk, fraud, or financial crime.
- Deep understanding of the machine learning lifecycle, from data ingestion and feature engineering to model training, deployment, monitoring, and experimentation.
- Strong technical background with experience in data processing, distributed systems, and relevant programming languages (e.g., Java, Python).
- Familiarity with applying advanced AI techniques, such as Generative AI and Large Language Models, to solve real-world problems, particularly in automating complex workflows or analyzing unstructured data.
- Experience working closely with non-technical stakeholders, such as operations teams, legal/compliance experts, and product managers.
- Excellent communication skills with the ability to articulate complex technical concepts and strategies to diverse audiences.
- Ability to balance short-term needs with a long-term strategic vision.
- Experience in hiring and developing technical talent.
- Experience in the fintech industry or working on payments/financial products.
- Specifically with financial crime detection (fraud, AML, KYC).
- Familiarity with relevant compliance regulations (e.g., AML, KYC, PSD2).
- Experience working with large datasets related to payments, identity, or transaction monitoring.
- Experience with open-source contributions or engaging with the broader tech community.