Engineering Manager, Safety Processing
Lead three engineering squads building automated LLM review pipelines, enforcement systems, appeals, and investigator tooling for Discord's Trust & Safety. Manage nine engineers while driving automation, compliance, and operational tooling in a high-stakes environment.
About the job
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
- 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: review a design, follow a hard incident, and disagree with an approach without taking the work away from senior engineers
- Experienced working alongside operations or human-in-the-loop teams; understand quality assurance, reviewer calibration, and appeals, and 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 you've managed want to work with you again
Bonus Points
- A strong passion for Discord and/or gaming, and an appreciation for the communities we serve
- Trust and safety, fraud, integrity, or abuse engineering at a consumer platform
- Building internal tools where operations or review teams are the primary user
- Consolidating fragmented legacy systems onto a single platform, or managing outsourced operations teams and vendors
Compensation
The US base salary range for this full-time position is $248,000 to $279,000 + equity + benefits.
Skills
LLMs, Backend, Distributed Systems, Machine Learning, Data Science
Similar jobs
Engineering Management jobsLeads a hands-on product engineering team building and operating polished, scalable software products. Requires 10+ years of software engineering experience, including 5+ years managing teams, with depth in full-stack development, distributed systems, reliability, and product quality.
Leads a team of Forward Deployed Engineers delivering and integrating physical AI systems for defense and government customers. Requires 8+ years of industry experience, recent technical leadership, production deployment experience, broad software and hardware expertise, and U.S. security-clearance eligibility.
Leads and scales engineering teams responsible for high-throughput social-data systems, real-time AI agents, analytics, and automation. The role combines people management, product execution, architecture oversight, delivery excellence, hiring, and cross-functional collaboration.
Leads and develops a customer-facing Applied AI Engineering team delivering production AI systems and sustained enterprise adoption. The role requires strong technical judgment, people leadership, executive communication, and experience scaling complex AI or software implementations.
Leads and scales a team of Applied AI Engineers helping strategic customers integrate Codex into software development workflows. Requires 8+ years in technical customer-facing roles, team leadership experience, and hands-on expertise with generative AI, software engineering, and production systems.