Senior Software Engineer- User Behavior

Overview

Build the backend systems that shift how Roblox responds to unsafe behavior, from reactive, stateless punishment to personalized, adaptive treatment based on each user's real risk profile.

What you'll do

• Build the User Behavior Foundation: design and operate the low-latency, per-user behavioral data layer that powers real-time safety decisions, aggregating signals such as 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.
• Own the Feature Restriction Platform: build a unified, backend-driven framework for delivering safety interventions that any product team can plug into, replacing 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.
• Ship code, not just designs: own end-to-end delivery from system design through migration, testing, and production operation.

What you'll need

• 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).

Details

• Location: San Mateo, CA, United States (headquarters).
• Onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday.
• Annual base salary range: $196,750 to $243,290 USD.
• Full-time employees are also eligible for equity compensation and benefits.
• US work authorization restrictions apply: the Company may not be able to employ candidates requiring certain U.S. visa categories or support future H-1B sponsorship.