Compliance Technology Program Lead

Block•Bay Area, CA, United States of America, CA

3d•$142,600 - $257,600•Remote

About The Position

Block is seeking a Compliance Technology Program Lead to ensure that machine learning and heuristic detection models, along with the data infrastructure supporting them, are fit for purpose for fiat and virtual currency products. The role operates at the intersection of compliance, machine learning, and AI tooling, using tools such as Claude and other LLM-based agents to automate oversight, monitoring, and documentation and make the program scalable and defensible. The position partners with Machine Learning, Engineering, BSA/AML Policy, and CAX stakeholders to provide end-to-end technical oversight, effective challenge, and ongoing monitoring across the model development lifecycle. It establishes model and data governance aligned with SR 11-7, SR 26-2, and OCC 2011-12; develops real-time monitoring dashboards and controls; and oversees transaction monitoring, blockchain analytics and screening, sanctions screening, customer risk scoring, and AI-driven case resolution models. The role ensures model decisions and changes are explainable, auditable, documented, and within risk appetite.

Requirements

At least 7 years of experience in compliance technology at regulated financial institutions or as a consultant working with financial institutions.
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.
Experience with 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 their transaction monitoring and sanctions screening considerations.
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.

Responsibilities

Use AI agents such as Claude and other LLM-based tools to automate oversight, monitoring, and documentation, including requirements drafting, exam-ready documentation, data quality monitoring, and model performance reporting.
Design human-in-the-loop checkpoints so 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.
Provide effective challenge throughout the model development lifecycle and partner with BSA/AML Policy and CAX stakeholders to ensure documentation is exam-ready.
Lead the design and development of real-time dashboards to monitor model health, input data, and ongoing model performance.
Set standards for threshold tuning and ongoing Below the Line (BTL) testing controls.
Establish frameworks and triggers for identifying model performance degradation and when tuning or deprecation is needed; partner on tuning and ensure changes are within risk appetite and defensibly documented.
Oversee Transaction Monitoring models, including heuristic and rules-based detection logic, threshold settings, below-the-line testing, and alert-feeding data pipelines.
Oversee blockchain analytics and screening tools, including TRM and Chainalysis, focusing on typology coverage, alert quality, and integration with downstream investigations.
Oversee Sanctions Screening models, including LexisNexis, 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 models that triage, enrich, or disposition alerts, ensuring decisions are explainable, auditable, and defensible to regulators.