Staff Software Engineer, Fraud
Remote • Foster City, CA • FullTime
Posted 2mo ago
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
The Fraud team is the front line defending Replit's platform from exploitation, detecting and shutting down phishing deployments, preventing cryptomining on free-tier infrastructure, stopping LLM token farming, and keeping bad actors from weaponizing the platform against our users. This is adversarial work where attackers adapt constantly, and you will build the detection systems, heuristics, and automated responses to stay ahead of them. This role offers unique experience applying AI to security problems in production, building guardrails for AI-generated code, detecting prompt injection attacks at scale, and using LLMs as a defensive tool against abuse. You will own problems end-to-end, from identifying emerging abuse patterns to shipping the systems that stop them at scale.
Responsibilities
- Design and implement LLM guardrails for AI-generated code and agent interactions.
- Build AI-powered detection systems using LLMs to identify malicious patterns and automate responses.
- Develop and operate abuse detection systems for phishing, cryptomining, account takeover, and financial fraud.
- Design automated response mechanisms to enforce platform policies.
- Manage the full abuse response lifecycle: detection, investigation, enforcement, and appeals.
- Analyze attack patterns using BigQuery and Hex to create new detection rules.
- Maintain and extend internal detection tools like Slurper and Netwatch.
- Integrate and tune security scanners (SAST, SCA) in CI pipelines with performance SLAs.
- Track abuse trends, measure detection effectiveness, and adapt defenses.
Requirements
- 8+ years of experience in security engineering, anti-abuse, trust & safety, or fraud detection.
- Strong programming skills in Python and/or TypeScript.
- Experience with SQL and large-scale data analysis (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, account takeover, credential stuffing, resource abuse.
- Clear communication skills for cross-functional collaboration.
Benefits
- Competitive Salary & Equity
- 401(k) Program with a 4% match (US Only)
- Health, Dental, Vision and Life Insurance
- Short Term and Long Term Disability
- Paid Parental, Medical, Caregiver Leave
- Flexible Time Off (FTO) + Holidays
- Commuter Benefits (In-Office Only)
- Monthly Wellness Stipend
- Autonomous Work Environment
- In Office Set-Up Reimbursement (In-Office Only)
- Quarterly Team Gatherings
- In Office Amenities (In-Office Only)