Adversarial Fraud Engineer — Global Consumer Trust

Develop and perform adversarial testing to identify how attackers and other nefarious agents may exploit Adobe’s externally facing products, APIs, customer journeys, and fraud controls. Uses software engineering, automation, data analysis, and adversarial techniques to recreate real-world attacks, test defenses, and identify control gaps.

• →Conduct adversarial testing of Adobe’s externally facing products, services, APIs, and fraud controls to identify how they may be exploited by fraudsters and other bad actors.
• →Recreate real-world fraud and abuse attacks to understand attack paths, identify control gaps, and determine how defenses can be circumvented.
• →Design and build automated testing tools and scripts using APIs, Python or similar languages to simulate fraud and abuse scenarios at scale.
• →Develop creative test scenarios across account creation, identity, payments, entitlements, APIs, and other customer and product experiences.
• →Test new and existing fraud prevention measures to determine their efficiency and find opportunities to strengthen detection and prevention.
• →Retest mitigations to validate that identified attack paths have been effectively addressed and identify potential alternative methods of circumvention.
• →Document attack methodologies, findings, and recommendations and help build repeatable adversarial testing capabilities.
• →Stay ahead of on emerging fraud, abuse, automation, and AI-enabled attack techniques and apply those findings to Adobe’s products and defenses.

• Strong software engineering or technical automation skills, with proficiency in Python or a similar scripting/programming language.
• Experience working with REST APIs, HTTP, authentication, web applications, automation frameworks, and modern cloud-based systems.
• Experience building scripts, tools, or automated workflows to test complex systems and behaviors.
• Must have: Python/similar programming, APIs/HTTP, automation, debugging, Git, data/SQL, proficiency in interpreting product architecture.
• Useful: JavaScript, cloud services, browser automation, authentication/identity systems, CI/CD, security testing tools.
• Strong understanding of fraud, abuse, cybersecurity, adversarial testing, or digital risk, with curiosity about how bad actors exploit products and controls.
• Strong analytical skills and experience using SQL, logs, telemetry, or other data sources to understand system behavior and evaluate test results.
• Ability to understand complex product architectures and work effectively with Product, Engineering, Fraud, and Security teams.
• Strong communication and documentation skills with the ability to translate technical findings into clear risks and actionable recommendations.

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