Staff Software Engineer - Merchant Fraud Prevention

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.

Staff Java Engineer - Merchant Fraud Prevention

As a Staff Software Engineer in the Merchant Fraud Prevention group, you will serve as the core architect and strategic engineering partner for our fraud detection and mitigation ecosystems. You will define the long-term technical vision across 2–3 engineering teams, ensuring our Platforms can detect and prevent evolving fraud vectors at scale. Beyond technical leadership, you will be a key force multiplier, acting as a strategic advisor to engineering leadership, bridging the gap between business strategy and execution, and actively mentoring and growing our senior Individual Contributors (ICs).

Responsibilities

• Technical Strategic & Architecture: 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.

• Leadership Partnership: 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.

• Product Strategy: Shape the strategic roadmap alongside the Director of Engineering, fellow Staff Engineers, and Product leadership.

• Cross-Team Alignment: 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.

• Talent Multiplier & Mentorship: Sponsor and mentor senior engineers, build clear growth paths, model high engineering standards, and foster a culture of engineering excellence and psychological safety.

• ML & Data Infrastructure Evolution: Partner with Data Science and ML Engineering so infrastructure supports fast model deployment, feature stores, and real-time inference, without compromising latency or reliability.

• Fraud Ops Collaboration : 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

Requirements

• Technical leader: A track record of setting technical strategy through architectural judgment and clear communication via influence, not organizational authority.

• Distributed Systems Expertise : Deep experience designing and operating large-scale, production-grade distributed systems with a focus on reliability, performance, and resilience.

• ML Systems Experience : Comfortable architecting the infrastructure layer around ML workloads (e.g., feature stores, real-time inference pipelines, model serving) even without being an ML practitioner yourself; strong appetite for close, ongoing collaboration with Data Science/ML Engineering.

• Operationally Minded : Experience partnering with operational teams (e.g., Fraud Ops, Compliance) to turn real-world investigative signals into scalable engineering solutions; basic familiarity with security-by-design and regulated data handling is a plus.

• Proactive relationship-builder: led partnerships across SWE, MLE, Product, Operations, and Compliance to align technical direction, drive clarity through ambiguity, and balance immediate product needs with long-term platform investments.

• Applied ML/AI Experience (nice to have): You have experience in building production-grade interfaces powered by LLMs, including harnesses, policy enforcement, evals, RAG architectures and secure data handling.

Our Diversity, Equity and Inclusion commitments

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen.

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

What’s next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here . Don’t be afraid to let us know if you need more flexibility.

This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.