Senior Software Engineer - Java - AML Handling

Description

You would join the AML Handling team, part of the AML Squad in the FinCrime Chapter.

Regulators expect more users reviewed, more typologies monitored, and decision quality raised every year. Adding investigators alone is costly and makes quality hard to hold, so the team uses technology to scale.

The team builds back-office tools that let agents work in one shared space, get AI help in their daily work, and have high-confidence cases resolved automatically.

The aim is to help operational teams work better by using automation and AI to support sound decisions, cut manual effort and reduce friction for customers.

The company is a global technology company that moves and manages money across borders, and it is building a new network for the world's money.

The team is international.

Responsibilities

• Design and build scalable systems for AML case handling and investigation.
• Take large technical initiatives from the initial problem through design, delivery and running in production.
• Work with Product, Operations, Data Scientists and Data Analysts to find opportunities, shape product choices and measure results.
• Build automation and put AI into production, with attention to quality, evaluation, traceability and suitable human oversight.
• Raise reliability, security and technical quality through system design, testing, code review and knowledge sharing.
• Work mainly with Java, Spring Boot and Kafka on SQL databases, running distributed services, asynchronous processing and large data volumes.
• Design for scalability, observability, privacy, security, reliability and cost.

Requirements

• 5+ years of experience building backend, distributed or data-intensive systems.
• Strong Java skills, with experience in Spring, relational databases and asynchronous messaging.
• Take ownership of outcomes, work through ambiguity, and lead initiatives from first idea to a reliable production solution.
• Think across the full stack, from backend services and data to the tools people use, and work across layers to solve problems end to end.
• Understand the needs of operational teams and customers, use data to guide decisions, and tie your work to measurable improvements.
• Use sound judgement to design for long-term change and scale, balancing delivery needs with maintainability and reliability.
• Explain technical trade-offs to non-technical partners and collaborate across engineering, product, operations and data.
• No prior AML experience is required. Curiosity and a willingness to learn are what count, and product leads, operational partners and data scientists will help you build domain knowledge.
• Nice to have: experience deploying machine learning or LLM-based systems in production, evaluating AI quality and cost, or building operational workflow and case management tools.

Conditions

The company aims for a diverse, equitable and inclusive workplace.