You will build the backend systems that fundamentally shift how Roblox responds to unsafe behavior - from reactive, stateless punishment to a personalized, adaptive system that reflects who a user actually is.

You will own core backend infrastructure for a new capability at Roblox: a low-latency behavioral data layer, a centralized rules-and-inference engine, and a unified intervention-delivery framework that together let us treat users based on their real risk profile instead of a single point total. This is a rare opportunity to build foundational, high-scale systems that directly shape how Roblox understands and responds to risk across hundreds of millions of users.

You will feel a deep sense of responsibility building systems that directly affect millions of users, especially minors, on one of the world's largest platforms. Your work will reduce harm, improve fairness, and help ensure Roblox remains a place where creativity and community can thrive safely.
You will:

• Build the User Behavior Foundation: Design and operate the low-latency, per-user behavioral data layer that powers real-time safety decisions - aggregating signals like violation history, in-game reports, and behavioral patterns into a single queryable source of truth.
• Own the Consequence Engine: Build and evolve the centralized decision engine that combines deterministic rules with ML risk signals into a single, consistent safety decision the authoritative system every consequence flows through.
• Own the Feature Restriction Platform: Build a unified, backend-driven framework for delivering safety interventions that any product team can plug into, replacing today's fragmented, feature-specific implementations.
• Unify Abuse Reporting: Build the backend that consolidates reporting channels into a single, scalable framework - integrating LLM-based classification, agentic review workflows, and ML models to improve report routing, prioritization, and reporter feedback while meeting global regulatory requirements.
• Design for trust and auditability: Build serving infrastructure that meets a high bar for explainability and fairness, since these systems directly determine consequences for millions of users.
• Ship code, not just designs: Own end-to-end delivery - from system design through migration, testing, and production operation.

You have:

• 5+ years of experience building and operating production backend systems at scale, ideally in Go or a comparable statically-typed backend language.
• Strong experience designing distributed systems: service APIs (RPC/gRPC), data modeling for high-throughput event ingestion, caching, and low-latency read paths.
• Experience building and evolving rules engines, workflow/decision systems, or similarly stateful business-logic services.
• Experience with streaming or batch data pipelines feeding a feature store or similar ingestion layer, and comfort partnering with ML engineers who consume that data.
• Solid production operations fundamentals: monitoring, alerting, oncall, capacity planning, and incident response for systems with real user-facing impact.
• Nice to have: experience in Trust & Safety, fraud, risk, or other adversarial domains; experience with feature stores or ML-serving infrastructure; experience building frontend-agnostic, backend-driven UI frameworks (e.g. server-driven intervention/notification rendering).

You are:

• A Systems Thinker: capable of designing infrastructure that other teams (ML, feature teams, policy) build on top of, not just point solutions.
• A Pragmatic Builder: scrappy and impact-oriented, comfortable turning scattered, undocumented signals and legacy code paths into clean, well-owned services.
• Comfortable with Ambiguity: this space is actively being redefined - you'll help set the standard, not just implement one handed to you.
• A Reliability-Minded Engineer: you treat testing, migrations, and oncall as first-class parts of the job, not afterthoughts.
• Committed to Ethical, Responsible Engineering: dedicated to building systems that are fair, auditable, and operate with the utmost responsibility toward user safety.

For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.

Annual Salary Range

$196,750-$243,290 USD

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).