Staff Software Engineer, Fraud

Responsibilities

• Design and implement LLM guardrails that detect abuse scenarios in AI-generated code and agent interactions
• Build AI-powered detection systems that use LLMs to identify malicious patterns, classify threats, and automate response decisions
• Build and operate abuse detection systems that identify phishing, cryptomining, account takeover, and financial fraud across millions of daily user actions
• Design automated response mechanisms that enforce platform policies without manual intervention
• Own the full abuse response lifecycle: detection, investigation, enforcement, and handling appeals alongside Support and Legal
• Analyze attack patterns using BigQuery and Hex, turning investigation findings into new detection rules
• Maintain and extend internal detection tools (Slurper, Netwatch) that continuously monitor user activity
• Integrate and tune security scanners (SAST, SCA) in CI pipelines with tight performance SLAs
• Track abuse trends, measure detection effectiveness, and adapt defenses as attack patterns evolve

Requirements

• 8+ years of experience in security engineering, anti-abuse, trust & safety, or fraud detection
• Strong programming skills in Python and/or TypeScript for building detection systems and automation
• Experience with SQL and data analysis at scale (BigQuery, Snowflake, or similar)
• Experience building or fine-tuning ML/LLM-based classifiers for security or abuse detection
• Familiarity with prompt injection, jailbreaking, and other LLM-specific attack vectors
• Ability to investigate complex abuse patterns and translate findings into automated defenses
• Familiarity with common attack patterns: phishing infrastructure, account takeover, credential stuffing, resource abuse
• Clear communication skills for working across Security, Support, Legal, and Engineering teams

Nice to Haves

• Experience at a platform company dealing with user-generated content or compute abuse (hosting providers, cloud platforms, developer tools)
• Background in fraud detection, payment abuse, or financial crime
• Familiarity with device fingerprinting, IP reputation, and email validation services
• Experience with CI/CD security tooling (SAST, SCA, Dependabot, Snyk)
• Knowledge of container security, Linux internals, or cloud infrastructure (GCP preferred)
• Prior work with abuse reporting pipelines, trust & safety tooling, or content moderation systems

Tech Stack

• Languages: Python, TypeScript, Go, SQL
• Data: BigQuery, Hex
• Detection tools: Slurper, Netwatch, Stytch (device fingerprint), ClearOut (email reputation)
• CI/CD Security: Dependabot, Snyk, SAST/SCA scanners
• Infrastructure: GCP, Kubernetes