Software Engineer, Trust & Safety (Distributed Systems)

About the position 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. 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 You'll architect and scale the trust infrastructure that keeps 70M+ users safe while preserving the creative freedom that makes Gamma magical. This means designing distributed systems for real-time content scanning, anomaly detection, and rate limiting; helping define and evolve the core data model and storage systems behind abuse detection; and shipping the high-volume event pipelines and internal tools that let our support teams act quickly on threats. You'll join a small, high-impact team building the foundation for trust at scale. You'll work across databases, public APIs, and event infrastructure, balancing long-term technical investments with rapid shipping velocity. 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.

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

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

Benefits

• benefits & equity

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