Senior Distributed Systems & Detection Engineer - Lisbon, Hybrid

ABOUT THE OPPORTUNITY

Join a Northern European AI-driven financial crime prevention scale-up expanding their Lisbon engineering hub. This is a rare opportunity to architect and build the core detection engine that processes large-scale financial data for leading financial institutions across Europe. The company is backed by top-tier investors and moving beyond traditional AML software toward intelligent automation and agentic AI systems that transform how banks fight financial crime.

PROJECT & CONTEXT

You'll be designing and building the detection engine from the ground up—the distributed system responsible for evaluating massive financial datasets, computing behavioral patterns, and executing detection logic at scale. This is greenfield architecture work on an Azure-native platform using modern data stack (Spark, Iceberg, Trino) combined with advanced AI capabilities. The engineering culture is design-first: architectural decisions are documented through RFCs and design docs before implementation, with focus on system-level thinking, reliability, and long-term maintainability. You'll work with a senior engineering team of 15+ experienced engineers, reporting directly to the VP of Engineering.

WHAT WE'RE LOOKING FOR (Required)

• 5+ years building distributed systems and data-intensive applications
• Deep hands-on experience with large-scale analytics engines (Spark, Iceberg, Trino, or similar)
• Proven ability to design deterministic, high-performance data pipelines
• Strong understanding of performance engineering and algorithmic complexity
• Experience with cloud-native architectures (Azure, AWS, or GCP)
• Track record of architectural ownership and system design leadership
• Fluent English (C1+), Portuguese is a plus
• Willingness to work hybrid model (1-3 days/week in Lisbon office)

NICE TO HAVE (Preferred)

• Experience with event-driven and message-oriented architectures
• Familiarity with AKS, Redis, Keycloak
• Background in financial services or regulated industries
• Experience with workflow automation systems
• Contributions to open-source data engineering projects
• Strong mathematical reasoning applied to real-world systems