Quantexa Developer (Multiple Locations) jobs in United States
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CyberX Info System · 1 day ago

Quantexa Developer (Multiple Locations)

CyberX Info System is seeking a Quantexa Developer specializing in Financial Crime to design and implement advanced decision-intelligence solutions for detecting and preventing financial crime risks. The role involves big data engineering, entity resolution, and graph analytics to enhance risk detection and investigation efficiency.

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Hiring Manager
Mohsin Nazir
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Responsibilities

Design and implement Quantexa-based AML/KYC/Fraud solutions using entity resolution, rules, scoring, and graph analytics
Develop detection logic aligned with financial crime typologies (e.g., TBML, layering, structuring, mule networks, sanctions evasion)
Translate AML and fraud risk requirements into technical specifications within the Quantexa platform
Build Spark-based ingestion pipelines for customer, account, transaction, and external intelligence data
Model entities and relationships for risk-based network views (customers → accounts → transactions → counterparties)
Optimize data transformations and graph structures to support Quantexa’s Contextual Monitoring and investigations
Configure and tune Entity Resolution (ER) rules, scoring models, risk indicators and typologies, alerting logic for contextual monitoring
Develop custom Scala/Java components to extend Quantexa functionalities when needed
Deploy Quantexa pipelines into cloud or on-prem environments
Integrate Quantexa output with downstream systems: case management, alerting, dashboards
Support performance tuning, troubleshooting, and production maintenance
Work with AML investigators, FIU analysts, and compliance SMEs to validate typologies, false positives, and risk scoring
Present technical solutions in business terms to compliance and risk stakeholders

Qualification

ScalaApache SparkQuantexa PlatformBig Data ecosystemsSQLAPIs integrationCloud platformsEntity resolutionGraph analyticsAgile deliveryFinancial crime knowledgeDockerKubernetesCAMS certificationML-based risk scoringCommunication skillsProblem-solving skillsCollaboration skills

Required

Strong proficiency in Scala or Java, with hands-on Apache Spark experience
Experience with data engineering and Big Data ecosystems (Hadoop, Hive, HDFS, Parquet)
Understanding of entity resolution, network analysis, and graph-based data models
SQL skills for data validation and data quality analysis
Experience integrating APIs, microservices, and ETL/ELT pipelines
Familiarity with AML and fraud typologies such as: Transaction structuring / layering, Trade-based money laundering, Sanctions circumvention, Watchlist matching, Synthetic identities, Account takeover / mule networks
Understanding of the AML lifecycle: onboarding/KYC, CDD/EDD, TM alerting, case investigation, SAR reporting
Experience with the Quantexa Decision Intelligence Platform (highly preferred)
Experience with cloud platforms (Azure/AWS/GCP) and CI/CD tools (Jenkins, GitLab, Azure DevOps)
Knowledge of Docker/Kubernetes is a plus
Ability to translate financial crime risk requirements into technical solutions
Strong analytical, problem-solving, and debugging skills
Excellent communication and collaboration across engineering, analytics, and compliance teams
Ability to work in agile delivery environments

Preferred

Experience with the Quantexa Decision Intelligence Platform (highly preferred)
Experience with cloud platforms (Azure/AWS/GCP) and CI/CD tools (Jenkins, GitLab, Azure DevOps)
Knowledge of Docker/Kubernetes is a plus
Knowledge of graph databases (Neo4j, TigerGraph)
Prior work with AML transaction monitoring systems (Actimize, SAS AML, Oracle FCCM)
Experience with ML-based risk scoring or anomaly detection
Certifications such as CAMS, ICA, or cloud certifications (Azure/AWS)

Company

CyberX Info System

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Cyberx Info System's unique brand differentiation is our relentless focus on customer-centric mobile app development.

Funding

Current Stage
Growth Stage

Leadership Team

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Rachel Noor
Company Owner
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Company data provided by crunchbase