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# Software Engineer

- **Company:** Ai, Inc
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $130,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Data Files, Database Applications, Fraud Prevention and Detection, Design of User Interfaces, Human-Computer Interaction, Software Engineering, Backend, Build Management
- **Published:** September 22, 2026
- **Apply:** https://www.careerbuilder.com/job-details/software-engineer-fraud-san-francisco-ca--3f41d01c-2f8b-4a82-a116-3e98e2ff5d45

## About the Role

* 4+ years of experience building production backend systems
 * Strong engineering fundamentals with experience in scalable system design and data-driven applications
 * Experience working on fraud detection, abuse prevention, or trust & safety systems (preferred but not required)
 * Ability to identify patterns in complex systems and translate them into technical solutions
 * High ownership mindset with comfort operating in fast-moving, ambiguous environments
 * Strong judgment in balancing risk, speed, and user experience

Preferred

 * Prior experience building fraud, risk, or trust & safety systems at scale
 * Familiarity with identity verification, anomaly detection, or behavioral analytics
 * Experience working with large datasets, event streams, or real-time detection systems
 * Background in high-growth startups or environments with rapid iteration cycles, Artificial Intelligence (AI), Building Systems, Data Sets, Establish Priorities, Fitness, Needs Assessment, Product Engineering, Production Systems, Risk, Risk Management, Safety Systems, Software Engineering, Startup, Systems Scalability, Team Lead/Manager, Training/Teaching, User Interface/Experience (UI/UX)

## Description

Location: San Francisco or New York CityCompany Stage: Series C / Late-Stage (AI / Enterprise)Office Type: Onsite (5 Days a Week)Salary: $130,000 - $400,000 + Equity, * Design and build fraud detection and prevention systems across key surfaces, including identity verification and platform abuse

 * Identify fraud patterns and translate them into scalable backend systems, tools, and workflows
 * Partner closely with product and engineering to define fraud strategy and prioritize high-impact initiatives
 * Develop systems that detect suspicious behavior, mitigate risk, and reduce fraudulent activity in real time
 * Improve visibility into fraud trends, risk exposure, and system effectiveness through monitoring and analytics
 * Operate autonomously in ambiguous environments, owning large problem areas end-to-end
 * Balance security, user experience, and operational efficiency when designing fraud prevention systems


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