Description
As a Sr Staff Engineer on Adobe's Risk Platform (ARP), you'll set the architectural direction for risk mitigation across Adobe. You'll define the standards, patterns, and long-term technical strategy that let ARP and Adobe stay ahead of fraud and abuse as it evolves.
Responsibilities:
- Architect systems built for the next three to five years of risk mitigation, while delivering impact iteratively and solving today's most important priorities along the way.
- Push the platform to the forefront of AI and ML to strengthen fraud and abuse detection.
- Lay the foundational building blocks of the Risk Platform that future risk-mitigation capability builds on, including the platform's shift toward event-driven, continuously-reasoning risk intelligence.
- Set architectural standards for risk-decisioning services that other teams across Adobe adopt.
- Share architectural thinking broadly, through design docs that become org-wide standards, white papers, tech talks, or cross-org design reviews.
- Simplify complex, interlinked systems into designs other teams can build on with confidence.
- Mentor senior and staff engineers across teams, growing the next generation of technical leaders.
Requirements:
- Bachelor's or advanced degree in Computer Science or related field, or equivalent experience; Master's preferred.
- 12+ years architecting high-scale, highly performant platforms, and leading the technical teams that build them.
- Deep understanding of AI and ML, both to strengthen fraud detection and to counter AI-powered attacks.
- Deep expertise in distributed systems and databases, including SQL, NoSQL, and DynamoDB-class stores.
- Track record architecting systems with multi-year relevancy, not just solving today's scaling or reliability problem.
- Experience with data lakes and large-scale data platforms like Databricks or Spark.
- Proven ability to influence engineering direction across teams and Business Units without formal authority.
- A track record of publishing or presenting technical work that shaped how others build.
Nice to have:
- Experience with graph databases or identity/relationship graphs applied to fraud or abuse detection.
- Device fingerprinting or AI agent design experience.
- A payments, commerce, or fraud background.
- Familiarity with regulatory and compliance constraints relevant to payments and fraud decisioning.
Benefits:
- Comprehensive benefits programs
- Opportunities for growth and professional development
- Collaborative and dynamic work environment