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SolomonEdwards · 5 days ago

Senior Technical Implementation Lead – AML & Fraud Transaction Monitoring Systems

United States

Contract

Remote

Senior Level, Lead/Staff

$100/hr - $125/hr

8+ years exp

SolomonEdwards is a full-service professional services firm offering consulting and operations support. They are seeking a Senior Technical Implementation Lead with expertise in Anti-Money Laundering and Fraud Transaction Monitoring Systems to design and optimize monitoring solutions for U.S. banking operations, ensuring compliance with regulatory expectations.

AccountingConsultingProfessional Services

Growth Opportunities

Hiring Manager

Karen Keen

Responsibilities

Lead the end-to-end implementation of AML and Fraud transaction monitoring systems, such as Actimize, Mantas, SAS AML, FICO, or Oracle FCCM

Design and develop data integration pipelines from core banking, payments, and customer data systems into AML/Fraud platforms

Oversee data mapping, cleansing, transformation, and enrichment processes to ensure high-quality inputs for transaction monitoring

Configure detection scenarios, thresholds, and machine learning models to optimize alert generation and reduce false positives

Implement real-time or batch-based data feeds, ensuring scalability and resilience for high-volume transaction processing

Serve as technical SME for AML/Fraud systems architecture, ETL processes, and alert workflows

Collaborate with business analysts, compliance officers, data engineers, and model validation teams to translate regulatory requirements into technical solutions

Lead technical design reviews, code reviews, and solution validation with cross-functional teams

Ensure system implementations comply with internal technology standards, security policies, and data governance frameworks

Define and execute UAT, SIT, and parallel run strategies for new AML/Fraud monitoring scenarios

Support model tuning, calibration, and back-testing using historical transaction data

Partner with Compliance and Operations to validate alert quality and investigative workflows

Drive production deployment, post-implementation validation, and ongoing system performance optimization

Ensure AML and Fraud systems align with BSA/AML, OFAC, FinCEN, and FFIEC guidelines

Provide technical documentation for audits, regulatory exams, and model risk management (MRM) reviews

Support internal and external examiners by explaining data lineage, detection logic, and scenario design

Qualification

AML/Fraud transaction monitoringData integration toolsProgramming languagesCloud & DevOpsFinancial crime typologiesModel risk governanceProfessional certificationsAnalytical skillsCommunication skillsLeadership skillsStrategic thinking

Required

Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or related field

8+ years of experience implementing or managing AML/Fraud transaction monitoring systems at a large financial institution or vendor

Hands-on experience with one or more AML/Fraud platforms: NICE Actimize (SAM, CDD, IFM, RCM modules), Oracle Mantas or FCCM, SAS AML, FICO or equivalent vendor solutions

Strong technical expertise in: Data integration tools: Informatica, Talend, Kafka, NiFi, or Spark; Databases: Oracle, SQL Server, Hadoop, Snowflake, or Teradata; Programming languages: SQL, Python, Java, or Scala; Cloud & DevOps: AWS, Azure, GCP, Kubernetes, CI/CD pipelines

Proven track record designing high-performance data pipelines for large-scale transaction monitoring

Deep understanding of financial crime typologies, AML/Fraud risk indicators, and KYC/CDD processes

Strong analytical and problem-solving skills with attention to detail

Excellent communication skills; ability to collaborate effectively across Compliance, Risk, and Technology teams

Proven ability to lead large-scale, multi-vendor technology projects in a regulated environment

Strategic thinker who can balance compliance requirements with technical feasibility

Preferred

Experience implementing real-time fraud detection systems using streaming data or machine learning models

Familiarity with regulatory frameworks such as BSA/AML, FATF, OFAC, and NYDFS Part 504

Experience with model risk governance and tuning of AML/Fraud detection scenarios

Professional certifications preferred: CAMS (Certified Anti-Money Laundering Specialist), CFE (Certified Fraud Examiner), AWS Certified Solutions Architect or Data Engineering certification