Full-stack AI Engineer

<div class="content-intro"><p>Ebury helps ambitious businesses unlock global growth, and we take the same approach with our people. We encourage innovation and movement, collaboration and problem-solving, and foster an environment where everyone can feel they belong, are valued, supported and empowered to succeed.</p> <p>If you’re a collaborator who wants to help transform how businesses operate globally, get in touch - we’d love to discuss how Ebury can accelerate your career so you can shape the future.</p></div><p><strong>Engineer</strong></p> <p><strong>London Office - Hybrid: 4 days in the office, 1 day working from home</strong></p> <p><strong>Senior Full-Stack Engineer - AI Agent Platform</strong></p> <p><strong>About the Role</strong></p> <p>We're building an AI-powered financial crime investigation platform that's transforming how Ebury's compliance teams work. Our AI agents will process thousands of screening cases, reducing analyst workload while maintaining regulatory standards.</p> <p>We're looking for a Senior Full-Stack Engineer to help us scale our platform and raise the engineering bar. You'll architect and deliver complex features across the entire stack - from React frontends to Python backends to LLM integrations - while mentoring teammates and shaping our technical direction.</p> <p>This is a unique opportunity to work at the intersection of AI/ML, fintech, and compliance - building production AI systems that handle real financial crime investigations at scale.</p> <p>&nbsp;</p> <p><strong>What You'll Do</strong></p> <ul> <li>Architect and build end-to-end features across our React frontend and FastAPI backend, making sound technical decisions that balance speed with maintainability</li> <li>Design AI agent workflows using LangGraph for screening automation, RAG pipelines, and multi-agent orchestration</li> <li>Lead technical initiatives - own complex features from design to production, breaking down ambiguous problems into actionable work</li> <li>Integrate complex data sources (internal APIs, third-party services like LexisNexis, data warehouse) with robust error handling and observability</li> <li>Improve platform reliability - implement monitoring, alerting, and performance optimizations for production AI systems</li> <li>Mentor and uplift junior and mid-level engineers through code reviews, pairing, and technical guidance</li> <li>Shape engineering practices - contribute to architecture decisions, coding standards, and team processes</li> <li>Collaborate cross-functionally with Product, Design, Compliance, and other engineering teams to deliver impactful solutions</li> </ul> &l