Job description

WHY THIS ROLE MATTERS NOW AI has dramatically lowered the barrier for bad actors. Generating convincing phishing pages, spinning up realistic-looking fraudulent accounts, and producing abusive content at scale no longer requires specialized skill—a motivated attacker with access to widely available models can do it. The volume and sophistication of platform abuse is increasing faster than traditional approaches can keep up with. At the same time, AI is transforming what's possible on the defensive side. A small, sharp T&S team equipped with frontier models can now build detection, triage, and response systems that would have required a team five times the size just a couple of years ago. AI-assisted content scanning, automated investigation workflows, and intelligent alert prioritization mean that a lean team can protect millions of users—if they build the right infrastructure. ABOUT THE ROLE Gamma is tackling one of the most critical challenges for any fast-growing AI platform: keeping millions of users safe while preserving the creative freedom that makes the product magical. As a Trust & Safety Engineer, you'll architect the systems that protect our platform from phishing, abuse, fraud, and malicious content, all while ensuring Gamma stays fast, reliable, and delightful to use. You'll join a small, high-impact team building the foundation for trust at scale. You'll design infrastructure that serves millions, ship improvements daily, and build the internal tools that let our support teams act quickly on threats. You'll collaborate across engineering, product, and design to define how Gamma approaches safety for the long term. Our team has a strong in-office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most. WHAT YOU'LL DO - Own detection and prevention systems for fraud, abuse, spam, and malicious content across millions of daily users - Design and build scalable trust infrastructure including rate limiting, content scanning, anomaly detection, and account security - Build tools that empower internal support teams to investigate and act on suspicious or malicious activity - Investigate and resolve complex security incidents with limited context - Partner with engineering and product to balance security with user experience - Shape Gamma's long-term trust and safety strategy and technical roadmap - Leverage AI/LLM-based detection to stay ahead of AI-generated abuse—phishing, fraud, and malicious content that's increasingly indistinguishable from legitimate activity - Build automated triage and investigation workflows that let a small team operate at the scale of a much larger one WHAT YOU'LL BRING - 5+ years as a software engineer with a focus on abuse, spam, or fraud prevention - Strong systems thinking and experience building highly available web APIs, with proficiency in at least one programming language and comfort working across a modern web stack - Hands-on experience implementing trust features like rate limiting, content detection, and fraud prevention - Experience with event streaming systems (Redis, Kafka, or similar) - Passion for security, user protection, and solving problems at scale NICE TO HAVE - Experience with AI/LLMs for content moderation, or familiarity with TypeScript, Prisma, Apollo GraphQL, or AWS - Experience building AI-assisted moderation pipelines or using frontier models for automated abuse detection and response - Familiarity with the evolving AI threat landscape—how generative models are being used for phishing, social engineering, and content abuse at scale COMPENSATION RANGE: The base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $180K - $310K plus benefits & equity. Final offer amounts are determined by multiple factors, including but not limited to experience and expertise in the requirements listed above. If you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.

Requirements

Must-haves

Our team has a strong in-office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most.
Own detection and prevention systems for fraud, abuse, spam, and malicious content across millions of daily users
Design and build scalable trust infrastructure including rate limiting, content scanning, anomaly detection, and account security
Build tools that empower internal support teams to investigate and act on suspicious or malicious activity
Investigate and resolve complex security incidents with limited context
Partner with engineering and product to balance security with user experience
Shape Gamma's long-term trust and safety strategy and technical roadmap
Leverage AI/LLM-based detection to stay ahead of AI-generated abuse—phishing, fraud, and malicious content that's increasingly indistinguishable from legitimate activity
Build automated triage and investigation workflows that let a small team operate at the scale of a much larger one
5+ years as a software engineer with a focus on abuse, spam, or fraud prevention
Strong systems thinking and experience building highly available web APIs, with proficiency in at least one programming language and comfort working across a modern web stack
Hands-on experience implementing trust features like rate limiting, content detection, and fraud prevention
Experience with event streaming systems (Redis, Kafka, or similar)
Passion for security, user protection, and solving problems at scale
The base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $180K - $310K plus benefits & equity.
If you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.

Nice-to-haves

Experience with AI/LLMs for content moderation, or familiarity with TypeScript, Prisma, Apollo GraphQL, or AWS
Experience building AI-assisted moderation pipelines or using frontier models for automated abuse detection and response
Familiarity with the evolving AI threat landscape—how generative models are being used for phishing, social engineering, and content abuse at scale

Application prep

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Keywords to mirror

aillmtypescriptgraphqlaws

Platform: ashby
Effort: quick