Jobs / research
Senior AI Research Engineer
Adyen · Amsterdam
What you will do
- Innovate and Deploy: Drive the execution of Adyen's AI strategy, focusing on the practical application of Generative AI (GenAI) and other AI methodologies in finance. This includes contributing to Adyen's efforts in key research areas such as AI agents for data analysis and operational workflows, human-in-the-loop for integrity risk, and development of foundation models. For instance, you might contribute to initiatives like the Data Agent Benchmark for Multi-step Reasoning (DABStep), which evaluates AI agents on real-world data analysis tasks, including those from the financial sector.
- Build Production-grade Applications: Bridge the gap between cutting-edge AI research and production by implementing research papers into robust, scalable, and production-ready code. Reduce complexity and dependencies across teams by championing engineering and scientific alignment by setting high quality standards.
- Optimize and Scale: Contribute to defining the long-term vision for AI at Adyen, specifically how AI will interact with humans and finance, including consumers, merchants, and financial institutions. This also includes understanding regulation and advocating for safe innovation in the field.
- Think Outside the Box: Drive innovation by challenging the status quo, introducing transformative ideas and implementing creative solutions to solve real-world problems. Carry out flexible, value-driven assignments, proactively unblocking teams to maximize organizational impact and drive strategic initiatives.
- Force Multiplier: Provide mentorship and horizontal sponsorship across the organization, fostering collaboration to share knowledge and best practices, and cultivating a culture of continuous improvement. This includes deeply engaging them in problem-solving processes and guiding them through execution, fostering their growth through hands-on involvement.
- Team Player: Actively pair with other engineering teams to solve deep-rooted technical challenges and be fully capable of being hands-on with the code, whether creating proof-of-concepts or fixing critical performance issues.
- Learn and Lead: Connect with the broader AI community (including startups, VCs, and AI labs) to stay informed of the latest advancements and identify potential partnership opportunities.