Member of Technical Staff - X Money, Fraud and Payments

xAI•Palo Alto, CA

14h•$180,000 - $440,000

About The Position

xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. We’re looking for an exceptional Software Engineer to focus on Fraud Engineering for a new payments platform being built at X which serves 600 million+ monthly users. This is a high-priority role responsible for protecting users and the platform from fraud, abuse, and risk. You’ll play a key role in designing and implementing systems to detect, prevent, and mitigate fraud in real time—at scale. Working at the intersection of security, distributed systems, and product engineering, you'll help build trusted payments infrastructure from the ground up.

Requirements

7+ years of backend or systems engineering, with exposure to fraud, risk, or abuse prevention systems preferred
Skilled in distributed systems: You’ve built resilient, high-throughput systems that operate under real-time constraints
Security-conscious: You understand threat models, data sensitivity, and defense-in-depth principles
Analytical and pragmatic: You value simple, high-leverage solutions and adapt quickly to evolving challenges
Builder mentality: You’re excited by zero-to-one problems and proven ability to thrive in fast-paced environments. You are willing to work hard.

Nice To Haves

Experience with real-time anomaly detection, machine learning for fraud, or rule-based risk systems
Familiarity with AML/KYC regulations, chargeback flows, or identity verification systems
Experience in fintech, trust & safety, or adversarial system design
Comfortable working in a zero-to-one environment with rapid iteration
Experience with: Golang, Postgres, Kafka, Memcached

Responsibilities

Design and implement fraud detection and prevention systems that operate at global scale and low latency
Develop risk scoring engines, anomaly detection pipelines, and real-time enforcement mechanisms
Collaborate with product, compliance, trust & safety, and infrastructure teams to ensure a secure and seamless user experience
Monitor and analyze fraud trends, and proactively respond to new attack vectors
Define engineering standards around observability, reliability, and rapid response in fraud-related systems