Jobs / United States / Adobe INC
Adversarial Fraud Engineer — Global Consumer Trust
Adobe INC · 🇺🇸 3 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 1,036 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 221 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Adobe INC paid sponsored hires in similar roles348 certified filings for “Software Development Engineer” (Software Developers) in CA: $174k–$227k, median $193k. Most were filed at wage level II (46%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Adobe INC
The US Department of Labor certified 1,036 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 221 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Adobe INC →
About the role
Designs and executes adversarial testing to identify how fraudsters and other bad actors 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. Partners with Fraud Prevention, Product, Engineering, and Security to translate findings into stronger defenses and retests mitigations to validate their effectiveness against evolving fraud and abuse techniques. What you’ll do • 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. • Partner with Fraud Prevention, Product, Engineering, Security, and other teams to understand threats, communicate findings, and recommend mitigations. • Test new and existing fraud controls to determine their effectiveness and identify 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 current on emerging fraud, abuse, automation, and AI-enabled attack techniques and apply those learnings to Adobe’s products and defenses. What you need to succeed • Bachelor's or Master's degree in Computer Science or a related field, plus 8+ years of hands-on industry experience. • 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, ability to understand 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. • An adversarial mindset with the creativity and persistence to identify alternative attack paths and methods of circumventing controls. • 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. • Strong judgment and commitment to conducting adversarial testing safely, responsibly, and within established authorization and testing boundaries. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personaliz