Cybersecurity Fraud Staff Engineer (Remote)
About the position
Responsibilities
• Own the technology strategy and architecture for fraud prevention related to AO and ATO across the enterprise.
• Design and implement risk-based authentication (RBA), step-up verification, and identity proofing solutions to mitigate fraudulent access attempts.
• Partner with fraud operations, cybersecurity, data science, and engineering teams to develop and deploy real-time fraud detection and prevention controls.
• Evaluate, select, and integrate best-in-class CIAM, fraud detection, and identity verification technologies (e.g., risk-based authentication, device intelligence, behavioral biometrics, bot mitigation).
• Develop machine learning-driven fraud models and signals to detect anomalies in identity-related behaviors.
• Collaborate with security and IAM teams to enhance MFA, passwordless authentication, and adaptive access policies.
• Build automated fraud orchestration capabilities that adapt in real time to emerging threats.
• Stay ahead of the latest fraud trends, including synthetic identity fraud, credential stuffing, and bot-driven ATO attempts.
• Guide engineering teams on secure coding practices to prevent vulnerabilities that could be exploited for fraud.
• Partner with external vendors and industry leaders to continuously enhance fraud defenses.
Requirements
• 8+ years of experience in identity fraud prevention, IAM/CIAM, security engineering, or fraud technology development.
• Strong expertise in Account Origination (AO) and Account Takeover (ATO) fraud prevention strategies.
• Hands-on experience with fraud prevention platforms, such as ThreatMetrix or similar.
• Deep knowledge of CIAM solutions like ForgeRock, Ping Identity, Microsoft Entra, or similar.
• Strong understanding of risk-based authentication, step-up authentication, and identity proofing technologies.
• Proficiency in anti-fraud techniques, including behavioral biometrics, device fingerprinting, bot mitigation, and anomaly detection.
• Experience implementing real-time fraud detection and risk scoring models using machine learning and behavioral analytics.
• Hands-on experience with APIs, microservices, and cloud-based architectures (AWS, GCP, or Azure).
• Strong programming/scripting skills in Python, Java, or similar languages for building fraud-related automation.
• Familiarity with industry standards and frameworks, such as NIST 800-63, PSD2, FIDO, and OpenID Connect.
• Ability to troubleshoot complex fraud patterns and lead engineering teams in designing effective countermeasures.
• Strong problem-solving, analytical, and communication skills with a passion for fighting fraud.
Nice-to-haves
• Experience with fraud signal aggregation and orchestration using tools like SAS, Feedzai, or custom ML models.
• Knowledge of synthetic identity fraud detection techniques.
• Experience designing and implementing zero-trust identity architectures.
• Hands-on experience with bot mitigation solutions, such as PerimeterX, Cloudflare Bot Management, or Akamai Bot Manager.
Apply Now
Apply Now
Responsibilities
• Own the technology strategy and architecture for fraud prevention related to AO and ATO across the enterprise.
• Design and implement risk-based authentication (RBA), step-up verification, and identity proofing solutions to mitigate fraudulent access attempts.
• Partner with fraud operations, cybersecurity, data science, and engineering teams to develop and deploy real-time fraud detection and prevention controls.
• Evaluate, select, and integrate best-in-class CIAM, fraud detection, and identity verification technologies (e.g., risk-based authentication, device intelligence, behavioral biometrics, bot mitigation).
• Develop machine learning-driven fraud models and signals to detect anomalies in identity-related behaviors.
• Collaborate with security and IAM teams to enhance MFA, passwordless authentication, and adaptive access policies.
• Build automated fraud orchestration capabilities that adapt in real time to emerging threats.
• Stay ahead of the latest fraud trends, including synthetic identity fraud, credential stuffing, and bot-driven ATO attempts.
• Guide engineering teams on secure coding practices to prevent vulnerabilities that could be exploited for fraud.
• Partner with external vendors and industry leaders to continuously enhance fraud defenses.
Requirements
• 8+ years of experience in identity fraud prevention, IAM/CIAM, security engineering, or fraud technology development.
• Strong expertise in Account Origination (AO) and Account Takeover (ATO) fraud prevention strategies.
• Hands-on experience with fraud prevention platforms, such as ThreatMetrix or similar.
• Deep knowledge of CIAM solutions like ForgeRock, Ping Identity, Microsoft Entra, or similar.
• Strong understanding of risk-based authentication, step-up authentication, and identity proofing technologies.
• Proficiency in anti-fraud techniques, including behavioral biometrics, device fingerprinting, bot mitigation, and anomaly detection.
• Experience implementing real-time fraud detection and risk scoring models using machine learning and behavioral analytics.
• Hands-on experience with APIs, microservices, and cloud-based architectures (AWS, GCP, or Azure).
• Strong programming/scripting skills in Python, Java, or similar languages for building fraud-related automation.
• Familiarity with industry standards and frameworks, such as NIST 800-63, PSD2, FIDO, and OpenID Connect.
• Ability to troubleshoot complex fraud patterns and lead engineering teams in designing effective countermeasures.
• Strong problem-solving, analytical, and communication skills with a passion for fighting fraud.
Nice-to-haves
• Experience with fraud signal aggregation and orchestration using tools like SAS, Feedzai, or custom ML models.
• Knowledge of synthetic identity fraud detection techniques.
• Experience designing and implementing zero-trust identity architectures.
• Hands-on experience with bot mitigation solutions, such as PerimeterX, Cloudflare Bot Management, or Akamai Bot Manager.
Apply Now
Apply Now