Software Engineer, Trust & Safety (Distributed Systems)

Gamma•San Francisco, CA

1d•$180,000 - $275,000•Hybrid

About The Position

This role is critical in addressing the increasing threat of AI-driven abuse, such as convincing phishing pages, fraudulent accounts, and malicious content. The Trust & Safety team leverages frontier AI models to build efficient detection, triage, and response systems. The successful candidate will architect and scale trust infrastructure to protect over 70 million users while maintaining the platform's creative freedom. This involves designing distributed systems for real-time content scanning, anomaly detection, and rate limiting, defining core data models for abuse detection, and developing high-volume event pipelines and internal tools for support teams. The role requires working across databases, public APIs, and event infrastructure, balancing long-term technical investments with rapid development. Collaboration with engineering, product, and design teams is essential to shape Gamma's long-term safety approach. The team fosters a strong in-office culture, working in person 4-5 days a week in San Francisco, with flexibility for focused remote work.

Requirements

5+ years of backend engineering experience building scalable, high-traffic production systems
Strong systems thinking and experience building highly available web APIs
Strong proficiency in backend technologies (Node.js, Python, or similar) and databases (PostgreSQL, Redis)
Experience with event streaming systems (Redis, Kafka, or similar) and high-volume event pipelines
Hands-on experience implementing trust features like rate limiting, content detection, and fraud prevention
Track record shipping high-quality, complex applications under tight timelines
Product-minded approach with understanding of how technical decisions impact user experience and business metrics
Passion for security, user protection, and solving problems at scale

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
Experience with real-time collaboration systems

Responsibilities

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
Architect distributed systems, APIs, and high-volume event pipelines that power real-time abuse detection at Gamma's scale
Help define and evolve the core data model and storage systems that underpin trust and safety across the product
Build tools that empower internal support teams to investigate and act on suspicious or malicious activity
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
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