Staff Software Engineer, Financial Crimes

Responsibilities

• Define the multi-year architecture for real-time entity-matching infrastructure, policy-enforcement engines, and reviewer tooling.
• Design and optimize distributed screening engines and detection pipelines handling entity- and transaction-level requests at scale with strict SLA and uptime guarantees.
• Build investigations infrastructure that surfaces suspicious activity, collects additional information from users, routes cases to reviewers, and augments human judgment with AI.
• Drive technical alignment with Legal, Compliance, ML, and Product leaders to translate evolving global regulatory requirements into technical requirements.
• Lead the architectural evolution toward a multi-tenant screening platform supporting internal products and external developer-facing APIs.
• Set standards for system design, API consistency, and operational rigor across backend and ML-adjacent systems; mentor senior engineers and lead high-stakes design reviews.
• Own reliability, observability, and latency, adapting production systems to changes in sanctions lists and traffic spikes; participate in an on-call rotation.

Requirements

• 10+ years of software engineering experience, including 5+ years in a strategic technical leadership role involving core infrastructure, distributed systems, or platform engineering.
• Experience designing, building, and operating high-throughput, low-latency APIs and distributed backend systems at scale.
• Track record of defining technical roadmaps and driving alignment across engineering teams and cross-functional domains.
• Hands-on technical depth, including system architecture, code-level performance tuning, and production debugging.
• Exceptional written and verbal communication skills, including the ability to articulate technical decisions to non-technical stakeholders.

Nice-to-haves

• Experience in financial crimes, sanctions screening, AML, entity resolution, or high-stakes trust and safety platforms.
• Experience applying LLMs or machine learning to operational workflows, fuzzy string matching, or NLP for entity matching.
• Experience building investigator or analyst tooling, case-management systems, or human-in-the-loop review workflows.
• Experience building platform products or APIs for internal engineering teams and external developers, including API backward compatibility and client libraries.
• Experience leading 0-to-1 platform builds or major architectural modernizations from concept to production.
• Experience with multi-language environments, primarily Ruby and Java, and modern data infrastructure.
• Comfort navigating ambiguity and making high-judgment engineering decisions in a fast-moving regulatory environment.