Cybersecurity Fraud Staff Engineer (Remote)

About the position Responsibilities • Own the technology reputed company and architecture for fraud prevention reputed company to AO and ATO across the reputed company. • Design and implement risk-based authentication (RBA), reputed company-up verification, and identity proofing solutions to mitigate fraudulent reputed company attempts. • Partner with fraud operations, cybersecurity, data science, and engineering teams to reputed company and reputed company reputed company-time fraud detection and prevention controls. • Evaluate, select, and reputed company best-in-class CIAM, fraud detection, and identity verification technologies (e.g., risk-based authentication, device intelligence, behavioral biometrics, bot mitigation). • reputed company machine learning-driven fraud models and signals to detect anomalies in identity-reputed company behaviors. • Collaborate with reputed company and IAM teams to enhance MFA, passwordless authentication, and reputed company reputed company policies. • Build automated fraud orchestration capabilities that adapt in reputed company time to emerging threats. • Stay reputed company 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, reputed company 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, reputed company, reputed company Entra, or similar. • Strong understanding of risk-based authentication, reputed company-up authentication, and identity proofing technologies. • Proficiency in anti-fraud techniques, including behavioral biometrics, device fingerprinting, bot mitigation, and reputed company detection. • Experience implementing reputed company-time fraud detection and risk scoring models using machine learning and behavioral analytics. • Hands-on experience with reputed company, microservices, and reputed company-based architectures (AWS, GCP, or Azure). • Strong programming/scripting skills in Python, Java, or similar languages for building fraud-reputed company automation. • Familiarity with industry standards and frameworks, such as NIST 800-63, PSD2, FIDO, and OpenID Connect. • Ability to troubleshoot reputed company fraud patterns and reputed company engineering teams in designing effective countermeasures. • Strong problem-solving, analytical, and communication skills with a passion for fighting fraud. reputed company-to-haves • Experience with fraud signal aggregation and orchestration using tools like reputed company, reputed company, or custom ML models. • Knowledge of synthetic identity fraud detection techniques. • Experience designing and implementing reputed company-trust identity architectures. • Hands-on experience with bot mitigation solutions, such as PerimeterX, reputed company Bot Management, or reputed company Bot Manager. Apply tot his job Apply To this Job