Requirements:

• Engineering Expertise: Strong experience building and operating production systems on Java/JVM, with expert-level knowledge of your technical discipline.
• Distributed Systems: Solid understanding of distributed systems and event-driven architectures (Kafka or similar), including designing for low latency, high availability, and scale.
• Technical Leadership: A track record of contributing significantly to large, impactful projects and owning their technical direction—from design and RFCs through delivery and long-term operation.
• Long-Term System Design: Experience designing systems with long-term iteration and scaling in mind, well-documented API-first interfaces, and a proactive approach to technical debt.
• Operational Excellence: Accountability for the reliability, security, and observability of the systems you build, including taking a leading role in incident resolution and post-incident reviews.
• Product Mindset: Ability to articulate why something is being built, what customer problem it solves, and what impact to expect, providing valuable feedback on the product roadmap to balance protection with low friction.
• Mentorship & Quality: Experience mentoring and coaching other engineers, helping raise the engineering bar through code reviews, design discussions, and best practices.
• Collaboration: Excellent communication skills to collaborate effectively across functions (Product, Data Science, Fraud Operations, Analytics).

Nice to Haves:

• Experience with Python, machine learning concepts, deploying models in production, or working with large language models in production.

What You'll Be Doing:

• Real-World Impact: Shape and build the systems that prevent fraud and scams through real-time transfer and profile decisioning.
• Technical Ownership: Own the technical roadmap and deliverables of key projects in our prevention domain, delivering them predictably and with clear customer impact.
• Domain & Platform Evolution: Build deep expertise across our technical and fraud domains, driving continuous improvements in latency, reliability, and decision quality across our decisioning platform.
• System Health: Address technical debt, keep risk within appetite, and enforce Wise's engineering best practices (observability, security, Kafka/DB usage, testing).
• Engineering Leadership: Multiply team impact by mentoring engineers, sharing knowledge to eliminate single points of failure, leading onboarding, and interviewing future talent.
• Cross-Team Collaboration: Contribute beyond the team through guilds and cross-team engineering efforts to reduce duplicated work across fraud and risk domains.

Perks and Benefits:

• The Fraud Risk team is a passionate group of prevention-focused crime fighters based in Budapest and Tallinn.
• A collaborative environment that encourages innovation, ownership, and teamwork.
• An exciting place to work on cutting-edge solutions in fraud prevention.