Staff Software Engineer - IPO (Identity & Performance Optimizations)

<h2><strong>This is Adyen</strong></h2> <p>Adyen is the financial technology platform of choice for leading businesses, providing payments, data, and financial products in a single solution for global customers like Meta, Uber, and H&amp;M. At Adyen, everything we do is engineered for ambition. We create an environment with opportunities for our people to succeed, backed by a culture that encourages ownership and provides the support to truly own your career. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team, delivering innovative and ethical solutions that help businesses achieve their ambitions faster.</p> <h3><strong>About the Role&nbsp;</strong></h3> <p>We are seeking a highly skilled and enthusiastic <strong>Staff Software Engineer</strong> with a strong background in building <strong>reliable</strong>, <strong>scalable</strong>, and <strong>low latency</strong> systems and hands-on experience in <strong>Machine Learning (ML) applications</strong>. In this role, you will play a critical part in designing, building, and scaling systems that leverage ML to solve real-world business challenges.</p> <p>You are someone who is <strong>curious about new technologies</strong>, <strong>eager to learn</strong>, and passionate about <strong>using technology as a practical tool</strong> to drive meaningful business impact. You enjoy solving complex problems and thrive in environments where innovation, continuous learning, and collaboration are key.</p> <h3><strong>The Opportunity&nbsp;</strong></h3> <p>Adyen is building out its capabilities in data-driven risk management to combat financial crime and fraud across its platform. We operate at a <strong>massive global scale</strong>, enabling businesses around the world to accept payments, issue cards, and embed financial products, helping <strong>millions of business owners around the globe do business with less friction</strong>. While we have foundational elements in place, we have recently shifted our strategy to take a more holistic approach to proactively detect and mitigate financial crime and fraud.&nbsp;</p> <h3><strong>Key Responsibilities</strong></h3> <ul> <li>Design and develop robust, scalable software systems that integrate Machine Learning models into production environments.</li> <li>Collaborate closely with product managers, data scientists, and business stakeholders to understand business problems and translate them into technical solutions.</li> <li>Evaluate new technologies, frameworks, and tools, and drive their adoption where appropriate to solve real business challenges.</li> <li>Mentor and guide junior engineers and peers through technical leadership and knowledge sharing.</li> <li>Advocate for best practices in software engineering, and system architecture.</li> <li>Continuously learn and stay up-to-date with advancements in software engineering, infrastructure, and AI technologies.</li> <li>Lead technical design discussions and contribute to the strategic direction of the technology roadmap.</li> <li>Close cross functional collaboration with different, non-technical functions like Account Management, Compliance, Operations etc.</li> </ul> <h3><strong>Requirements</strong></h3> <ul> <li><strong>At least 10-12 years of extensive industry hands-on experience in Software Engineering and building data intensive applications,</strong> including system design, architecture, and development.<strong>&nbsp;</strong></li> <li>Experience with building<strong> scalable, reliable, </strong>and<strong> low latency </strong>systems<strong>.</strong></li> <li>Strong programming skills in <strong>Java</strong>. (Python is a plus)</li> <li>Experience in <strong>incident management</strong>.</li> <li>Experience working with and using <strong>SQL</strong> and <strong>NoSQL</strong> databases like Postgres and Cassandra.</li> <li>Knowledge of <strong>streaming &amp; queuing </strong>frameworks.&nbsp;</li> <li>Deep curiosity and drive to continually <strong>learn new technologies</strong> and techniques.</li> <li>Familiarity with data engineering concepts, big data tools (like Spark), and distributed data architectures.</li> <li>Passion for applying technology to solve <strong>real business problems</strong> in a pragmatic and impactful way.</li&