Senior Software Engineer, Anti-Abuse & Security
Security Engineer ยท Senior ยท Full Time
Opens Replit's application page
Role
What you'll do.
Replit is seeking a Senior Software Engineer for their Anti-Abuse & Security team to defend their AI-native platform from exploitation and build cutting-edge detection systems. This role involves working on unique challenges like AI-generated code security, prompt injection detection, and using LLMs as defensive tools in a hybrid environment at Foster City, CA.
Responsibilities
- LLM Guardrails Development: Design and implement LLM guardrails that detect abuse scenarios in AI-generated code and agent interactions
- AI-Powered Detection Systems: Build AI-powered detection systems that use LLMs to identify malicious patterns, classify threats, and automate response decisions
- Multi-Vector Abuse Detection: Build and operate abuse detection systems that identify phishing, cryptomining, account takeover, and financial fraud across millions of daily user actions
- Automated Response Design: Design automated response mechanisms that enforce platform policies without manual intervention
- End-to-End Abuse Response: Own the full abuse response lifecycle: detection, investigation, enforcement, and handling appeals alongside Support and Legal
- Attack Pattern Analysis: Analyze attack patterns using BigQuery and Hex, turning investigation findings into new detection rules
- Detection Tool Maintenance: Maintain and extend internal detection tools (Slurper, Netwatch) that continuously monitor user activity
- Security Scanner Integration: Integrate and tune security scanners (SAST, SCA) in CI pipelines with tight performance SLAs
- Trend Monitoring and Adaptation: Track abuse trends, measure detection effectiveness, and adapt defenses as attack patterns evolve
Qualifications
What we look for.
Technical
Security Engineering Experience
4+ years of experience in security engineering, anti-abuse, trust & safety, or fraud detection
Programming Proficiency
Strong programming skills in Python and/or TypeScript for building detection systems and automation
Large-Scale Data Analysis
Experience with SQL and data analysis at scale (BigQuery, Snowflake, or similar)
ML/LLM Classification
Experience building or fine-tuning ML/LLM-based classifiers for security or abuse detection
LLM Security Knowledge
Familiarity with prompt injection, jailbreaking, and other LLM-specific attack vectors
Investigation and Automation
Ability to investigate complex abuse patterns and translate findings into automated defenses
Attack Pattern Recognition
Familiarity with common attack patterns: phishing infrastructure, account takeover, credential stuffing, resource abuse
Experience
Security Engineering
4+ years of hands-on experience in security engineering, anti-abuse, trust & safety, or fraud detection roles
Cross-Team Collaboration
Clear communication skills for working across Security, Support, Legal, and Engineering teams
Skills
Required
Python Programming
Advanced proficiency in Python for building detection systems and automation tools
TypeScript Development
Strong TypeScript skills for full-stack detection system development
SQL and Data Analysis
Expert-level SQL skills and experience with large-scale data analysis platforms
Machine Learning
Hands-on experience building and fine-tuning ML/LLM-based classifiers for security applications
LLM Security
Deep understanding of prompt injection, jailbreaking, and LLM-specific attack vectors
Threat Investigation
Advanced skills in investigating complex abuse patterns and translating findings into automated defenses
Attack Pattern Recognition
Comprehensive knowledge of phishing infrastructure, account takeover, credential stuffing, and resource abuse
Preferred
Platform Security Experience
Nice to haveExperience at platform companies dealing with user-generated content or compute abuse
Fraud Detection Background
Nice to haveBackground in fraud detection, payment abuse, or financial crime
Device Fingerprinting
Nice to haveFamiliarity with device fingerprinting, IP reputation, and email validation services
CI/CD Security Tools
Nice to haveExperience with CI/CD security tooling (SAST, SCA, Dependabot, Snyk)
Infrastructure Security
Nice to haveKnowledge of container security, Linux internals, or cloud infrastructure (GCP preferred)
Trust & Safety Systems
Nice to havePrior work with abuse reporting pipelines, trust & safety tooling, or content moderation systems
Tech stack
Languages
Databases
Tools
Other
Compensation
Pay and benefits.
BaseยทUSD 190,000 โ 240,000
EquityยทStock options
Benefits
Competitive Salary & Equity
Competitive compensation package including equity ownership
401(k) Program
Retirement savings plan with 4% company match
Health Insurance
Comprehensive health, dental, vision and life insurance coverage
Disability Insurance
Short-term and long-term disability coverage
Parental Leave
Paid parental, medical, and caregiver leave
Commuter Benefits
Transportation assistance and commuter support
Wellness Stipend
Monthly wellness allowance for health and fitness
Autonomous Work Environment
Flexible work arrangements and autonomy
Office Setup Reimbursement
In-office setup reimbursement for equipment and workspace
Flexible Time Off
Flexible Time Off (FTO) policy plus holidays
Team Gatherings
Quarterly team gatherings and events
Office Amenities
In-office amenities and facilities
Process
Interview steps.
- 01
Initial Screening
Phone or video call to discuss background, experience, and interest in the role
- 02
Technical Interview
Deep dive into security engineering experience, detection system design, and problem-solving approach
- 03
System Design Interview
Design an anti-abuse detection system or LLM security guardrails architecture
- 04
Case Study Discussion
Analysis of real-world abuse scenarios and discussion of investigation and mitigation strategies
- 05
Final Interview
Cultural fit assessment and discussion with team members about collaboration and communication skills
Full posting
Original listing.
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation.
About the role
The Anti-Abuse team is the front line defending Replit's platform from exploitation. We detect and shut down phishing deployments, prevent cryptomining on free-tier infrastructure, stop LLM token farming, and keep bad actors from weaponizing the platform against our users. This is adversarial work: attackers adapt constantly, and we build the detection systems, heuristics, and automated responses that stay ahead of them.
What makes this role unique is the AI-native nature of Replit's platform. You'll work on problems that barely exist elsewhere: building guardrails for AI-generated code, detecting prompt injection attacks at scale, and using LLMs as a defensive tool against abuse. If you want hands-on experience applying AI to security problems, this is one of the few places you can do it in production with real attackers. You'll own problems end-to-end, from identifying emerging abuse patterns to shipping the systems that stop them at scale.
In this role you willโฆ
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
Required skills and experience:
4+ 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 have:
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
Tools + Tech Stack for this role
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
Collaboration: Linear, Slack, Zendesk (for abuse reports)
This role may not be a fit if
You prefer deep security research over building operational detection systems
You want to focus on vulnerability management, pentesting, or bug bounty triage (that's our Security team)
You're looking for a role with predictable, well-defined problems rather than constantly adapting to adversarial behavior
You prefer working in isolation rather than partnering closely with Support, Legal, and cross-functional teams
You're uncomfortable making enforcement decisions that affect real users
This is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday.
Full-Time Employee Benefits Include:
๐ฐ Competitive Salary & Equity
๐น 401(k) Program with a 4% match
โ๏ธ Health, Dental, Vision and Life Insurance
๐ฉผ Short Term and Long Term Disability
๐ผ Paid Parental, Medical, Caregiver Leave
๐ Commuter Benefits
๐ฑ Monthly Wellness Stipend
๐งโ๐ป Autonomous Work Environment
๐ฅ In Office Set-Up Reimbursement
๐ Flexible Time Off (FTO) + Holidays
๐ Quarterly Team Gatherings
โ In Office Amenities
Want to learn more about what we are up to?
Interviewing + Culture at Replit
To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.
Redirects to Replit's application page.
Other roles
More at Replit.
Data Scientist, Trust & Safety
Senior
Product Engineer, Product Platform (Frontend)
Senior
Head of Forward Deployed Engineering
Lead
Senior Software Engineer, Fraud
Senior
Engineering Manager, Anti-Abuse & Security
Manager