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 tot his job Apply To this Job