Engineering Manager, Safety Processing

Discord·San Francisco Bay Areasenior

In short

→Liderar un equipo de ingeniería que automatiza revisiones de contenido con IA para mantener la seguridad en Discord.
→Trabajar en sistemas de justicia automatizados, apelaciones y herramientas para investigadores, con enfoque en precisión y escalabilidad.
→Destacado: los sistemas actuales ya redujeron el costo por revisión en más del 90% y superan a humanos en precisión.

None (no language requirement mentioned)

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What they ask for

✓5+ años como ingeniero de software con experiencia en backend y sistemas distribuidos
✓2+ años gestionando equipos de ingeniería
✓Experiencia en sistemas de LLM en producción que toman decisiones reales
✓Capacidad técnica para entender diseños, incidentes y discutir arquitectura sin quitar trabajo a equipos senior
✓Experiencia trabajando con equipos operativos o humanos en el bucle (QA, calibración, apelaciones)
✓Habilidades probadas en comunicación, colaboración cruzada y liderazgo de personas

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

LLMbackenddistributed systemsproduction systemsautomationenforcementappealstoolingreview systemsregulatory compliance

Who should you write to at Discord?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. This team is where reports and signals become decisions. We build the LLM pipelines that review reported content, the systems that carry enforcement out, the appeals path users take when we get it wrong, and the tooling our investigators and content reviewers work in every day. Most safety reviews are now decided by automation instead of a person, at a cost per review that has fallen by more than 90% on mature workflows and at precision and recall above trained human reviewers. What s left to automate is the ambiguous, high-stakes end, and with appeals arriving by the hundreds of thousands, getting users a fast and fair answer matters as much as catching harm. We re hiring an Engineering Manager to lead the team: nine engineers across three squads, each with an experienced tech lead. One builds the automated review systems; another owns enforcement, warnings, and the infrastructure behind appeals; and the final owns tooling that enables analysts to be effective. You ll report to the Director of Engineering for Safety and work closely with our content review operations, machine learning, product, policy, and legal teams. The charter is larger than the current headcount, and we expect the role to grow with it. What you ll do • Lead three squads, Review, Enforce, and Tooling through their tech leads, setting direction across automated review, enforcement, and appeals • Push automation toward nearly all review decisions without giving up precision or recall against a human baseline, and get engineering out of the loop so the operations team can launch and tune workflows themselves • Rebuild appeals: one path for every eligible appeal regardless of what triggered the original action, review tooling that scores decision quality rather than only flagging that two reviewers disagreed, and checks that catch mistakes before they land on good users • Own the tooling our investigators depend on, cutting complex investigations from hours to minutes, and make enforcement traceable enough that anyone can see how a user reached their current state • Carry regulatory and child-safety compliance work alongside the roadmap, set the engineering bar with your leads, and hire and grow the team Who you are • 5+ years as a software engineer with a solid backend and distributed systems background, and 2+ years managing engineers • You ve shipped LLM systems in production where the output is a decision the business acts on rather than a suggestion, with opinions about evaluation, ground-truth data, quality regressions, and where cost and latency start to bite • Technical enough to stay in the details. You can review a design, follow a hard incident, and disagree with an approach without taking the work away from senior engineers who know the system better than you do • Experienced working alongside operations or human-in-the-loop teams. You understand quality assurance, reviewer calibration, and appeals, and you build tools that respect the people using them • Steady under escalation. Legal deadlines, serious incidents, and regulator attention come with this job, and you can hold a quality line while shipping against a clock • Excellent communication and cross-functional collaboration across engineering, machine learning, data science, policy, legal, and product, and practical about throughput and unit economics • An empathetic and experienced recruiter and coach. People

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