Job Description Job Description About xAI 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 engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. About the role 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. What You'll Do 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 Who You Are Experienced: 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. Bonus 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 Tech Stack (Optional) Golang Postgres Kafka Memcached Interview Process After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 30 minute phone interview, during which a member of our team will ask technical questions. If you clear the phone interview, you will proceed to next steps: Coding assessment in a language of your choice. Systems design: Translate high-level requirements into a scalable, fault-tolerant service. Project deep-dive: Present your past exceptional work to a small audience. Meet and greet with the wider team. Our goal is to finish the main process within one week. Location The role is based in Palo Alto. Candidates are expected to be located near the Bay Area or open to relocation. Annual Salary Range $180,000 - $440,000 USD Benefits Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. xAI is an equal opportunity employer. California Consumer Privacy Act (CCPA) Notice

Required qualifications:

• 7+ years of backend or systems engineering
• Exposure to fraud, risk, or abuse prevention systems
• Skilled in distributed systems
• Security-conscious
• Analytical and pragmatic
• Builder mentality

Desired qualifications:

• 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