Senior Technical Implementation Lead - AML & Fraud Transaction Monitoring Systems

About Us

Solomon Edwards Group , LLC (“Solomon Edwards”) is a full-service professional services firm offering financial, operational, and technology consulting and operations support. We work with some of the world’s most prominent companies to help them envision and achieve a better future. We know that our consulting services are only as meaningful as the people and talent behind them, and we are committed to recruiting incredibly talented, committed, and collaborative individuals who can help us deliver exceptional client service.

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Position Summary:

We are seeking a Senior Technical Implementation Lead with deep expertise in Anti-Money Laundering (AML) and Fraud Transaction Monitoring Systems to design, implement, and optimize enterprise-scale monitoring solutions across our U.S. banking operations. This individual will play a key role in delivering technology solutions that strengthen our Client’s financial crime detection capabilities, align with regulatory expectations (BSA/AML, OFAC, FFIEC), and integrate seamlessly with core banking and data platforms.

Essential Duties:

System Implementation & Integration

• 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.

Technical Leadership

• 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.

Testing, Validation & Deployment

• 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.

Regulatory & Audit Support

• 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.

Qualifications:

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 & Dev Ops: 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.

Preferred Qualifications:

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…