Compliance Technology Program Lead

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

The Role

Block is seeking a Compliance Technology Program Lead to ensure our Machine Learning and Heuristic detection models — and the data infrastructure that feeds them — are fit for purpose, for our fiat and virtual currency products. This role sits at the intersection of compliance, machine learning, and AI tooling: you will use modern intelligence tools, including Claude and other LLM-based agents, to automate significant portions of oversight, monitoring, and documentation work — turning a traditionally manual, documentation-heavy function into a scalable, defensible program. You will partner with Machine Learning, Engineering and BSA/AML Policy Teams to provide end-to-end technical oversight, effective challenge and ongoing monitoring throughout the model development lifecycle.

You Will

• Build with Modern AI Tools: Use AI agents (Claude and similar LLM-based tools) to build automation that scales oversight, monitoring, and documentation work — including drafting requirements, exam-ready documentation, data quality monitoring and ongoing model performance reporting.
• Design human-in-the-loop checkpoints so that automated outputs remain defensible to regulators and independent monitors.
• Establish and maintain model and data governance frameworks aligned with SR 11-7, SR 26-2, and OCC 2011-12 so engineering teams can ship defensible models at pace. Provide effective challenge throughout the model development lifecycle and partner with the BSA/AML Policy Team and CAX stakeholders to ensure documentation is exam-ready.
• Lead Ongoing Monitoring: Lead the design and development of real-time dashboards to monitor model health, including input data monitoring and ongoing model performance.
• Set standards for threshold tuning and ongoing Below the Line (BTL) testing controls.
• Establish frameworks and triggers for identifying when model performance is degrading and requires tuning or deprecation. Partner during subsequent tuning exercises and ensure changes are within risk appetite and documented defensibly.
• Provide End-to-End Oversight of Model Development: Oversee Transaction Monitoring models, including heuristic and rules-based detection logic, threshold settings (below the line testing), and the data pipelines that feed alerts.
• Oversee blockchain analytics and screening tools (TRM, Chainalysis), with attention to typology coverage, alert quality, and integration with downstream investigations.
• Oversee Sanctions Screening models (LexisNexis), including list management, fuzzy-match tuning, and false-positive reduction.
• Oversee Customer Risk Scoring models, including segmentation logic, periodic recalibration, and effective challenge of risk drivers.
• Oversee the design and validation of AI-driven case resolution — LLM-based and ML-based models that triage, enrich, or disposition alerts — ensuring decisions are explainable, auditable, and defensible to regulators.

You Have

• 7+ years of experience in compliance technology at regulated financial institutions, or as a consultant working with FIs.
• Hands-on experience building with modern AI tools — including Claude, GPT, or comparable LLM-based agents — and a track record of using them to automate work in production. This includes prompt engineering, designing agentic workflows, and integrating AI into operational processes.
• Experience with both Machine Learning and Heuristic models across Transaction Monitoring, Sanctions Screening, and Customer Risk Scoring.
• Experience with input data quality monitoring.
• Experience with model performance monitoring.
• Experience conducting AML model validations aligned with SR 11-7 and OCC 2011-12.
• Experience responding to examinations and consent orders, and working with regulators and independent monitors.
• Experience with virtual currencies, including the unique transaction monitoring and sanctions screening considerations they present.
• Familiarity with blockchain analytics and screening tools such as Chainalysis and TRM Labs.
• A track record of driving cross-functional initiatives.
• A working understanding of regulated financial services and corresponding compliance obligations.
• Familiarity with statistical concepts related to machine learning
• Expertise in data analytics and visualization
  
  

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page.

While there is no specific deadline to apply for this role, U.S. roles are typically open for an average of 55 days before being filled by a successful candidate. Please refer to the date listed at the top of this job page for when this role was first posted.