FRAUD PREVENTION STAFF ENGINEER (AI & DECISION SYSTEMS)

Position Purpose:

The Staff Fraud Engineer owns the design, implementation, and evolution of the enterprise fraud prevention technology stack, delivering scalable, real-time defenses across all channels. This role leads the technical strategy and architecture for AI-driven fraud decisioning, integrating best-in-class platforms and advanced analytics to detect and prevent emerging threats. As a hands-on technical leader, the position drives development of high-availability, high-performance fraud systems through direct coding, system design, and optimization. The role partners closely with fraud analysts, investigators, data scientists, and engineers to continuously adapt solutions to new attack vectors, while mentoring peers and championing innovation in fraud prevention technologies.

Key Responsibilities:

• 100% Deliver Execution, Plans & Aligns, Develop Others – Design, review and execute solutions to protect the enterprise; Lead, mentor and provide guidance; Facilitate vulnerability management programs across systems, networking and engineering teams; Develop, test, deply and operationalize security monitoring, assessment and response solutions

Direct Manager/Direct Reports:

• This position typically reports to Manager or Sr. Manager
• This position has 0 Direct Reports

Travel Requirements:

• No travel required.

Physical Requirements:

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications:

• Hands-on experience integrating and implementing fraud prevention platforms such as ThreatMetrix, Ekata, Forter, Kount, or similar.
• Architectural fluency in data pipelines (Kafka, Spark, ETL frameworks), APIs, and microservices for fraud signal ingestion and scoring.
• Experience with cloud platforms (AWS, GCP, or Azure) and microservices architecture.
• Strong knowledge of data structures, AI/ML implementation, and real-time data processing.
• Proven track record building and operationalizing real-time scoring pipelines for Account Takeover (ATO) and Account Origination (AO) fraud.
• Expertise in designing scalable fraud decision engines and rule orchestration layers.
• Strong background in digital fraud mitigation techniques—including device fingerprinting, IP reputation, velocity/rule checks, and anomaly detection—ideally in an e-commerce or retail context.

Minimum Education:

• The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.

Preferred Education:

• No additional education

Minimum Years of Work Experience:

• 8

Preferred Years of Work Experience:

• No additional years of experience

Minimum Leadership Experience:

• None

Preferred Leadership Experience:

• None

Certifications:

• None

Competencies:

• Action Oriented
• Collaborates
• Drives Engagement
• Communicates Effectively
• Customer Focus
• Drives Results
• Manages Conflict