Remote Senior AML/CTF Investigator - AI-Enhanced

Coinbase, Inc.

United Kingdom

Remote

GBP 56,000 - 62,000

Full time

3 days ago

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Job summary

Coinbase, Inc. in the United Kingdom is seeking a Senior SAM Analyst in the CX Compliance team to lead AML/CTF investigations, manage high-risk cases, and ensure regulatory reporting with rigorous human oversight.

You will apply open-source research, identity checks, and blockchain analysis when needed to strengthen investigations. You will evaluate AI-generated narratives and risk assessments, provide feedback for product and ML engineering, and help drive model tuning and launch readiness

Qualifications

4+ years of experience in AML, transaction monitoring, fraud investigations, or financial crime compliance.
Bachelor’s degree or equivalent practical experience.
Demonstrated experience drafting and reviewing SARs/STRs and defending investigative conclusions through documented evidence and applicable regulatory requirements.
Experience conducting quality reviews, second-reviewer checks, calibration, user acceptance testing, or model evaluation, including identifying systemic weaknesses and communicating reproducible, actionable findings.
Demonstrated ability to prioritize competing cases and make risk-based escalation decisions under ambiguity or time pressure.
Preferred: CAMS or another relevant AML, fraud, or crypto investigation certification; experience with SQL, Snowflake, fraud-ring analysis, entity resolution, or blockchain analytics.
Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.

Responsibilities

Own end-to-end anti-money laundering and counter-terrorist financing (AML/CTF) investigations involving complex alerts, referrals, fraud typologies, and interconnected customer activity, including open-source research, identity verification, prior filing reviews, and blockchain analysis where needed.
Draft and review investigative narratives and Suspicious Activity Reports/Transactions Reports (SARs/STRs), ensuring conclusions are evidence-based, clearly documented, and consistent with applicable requirements.
Evaluate AI-generated narratives, evidence, risk assessments, and recommended dispositions using human-in-the-loop (HITL) quality scorecards to capture missed risk indicators, unsupported or fabricated facts, incorrect risk weighting, and inappropriate escalation decisions.
Translate recurring investigation, model, data, and workflow defects into actionable feedback for Product, Compliance Technology, and ML Engineering.
Support AI evaluation and release testing through annotation, calibration, user acceptance testing, and curated benchmark case reviews that inform model tuning and launch-readiness assessments.
Escalate material issues affecting customers, regulatory filings, control effectiveness, or launch readiness, documenting evidence, potential impact, and recommended next steps.