Senior Software Engineer (User Behavior)

Roblox as a Senior Software Engineer (User Behavior) and play a crucial role in shaping how the platform responds to unsafe behavior. You will build foundational, high-scale systems that directly impact millions of users, especially minors. Your work will reduce harm, improve fairness, and help ensure Roblox remains a safe space for creativity and community. You will own core backend infrastructure, design and operate a low-latency behavioral data layer, and build a centralized decision engine. This is a unique opportunity to make a significant impact on one of the world's largest platforms.

Concevoir et exploiter la couche de données comportementales par utilisateur à faible latence qui alimente les décisions de sécurité en temps réel.

Construire et faire évoluer le moteur de décision centralisé qui combine des règles déterministes avec des signaux de risque ML en une seule décision de sécurité cohérente.

About Roblox

Construire un cadre unifié, piloté par le backend, pour la livraison des interventions de sécurité que toute équipe produit peut intégrer.

Committed to Ethical, Responsible Engineering: dedicated to building systems that are fair, auditable, and operate with the utmost responsibility toward user safety

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)

A Reliability-Minded Engineer: you treat testing, migrations, and oncall as first-class parts of the job, not afterthoughts

A Pragmatic Builder: scrappy and impact-oriented, comfortable turning scattered, undocumented signals and legacy code paths into clean, well-owned services

Responsibilities

• 5+ years of experience building and operating production backend systems at scale, ideally in Go or a comparable statically-typed backend language
• Solid production operations fundamentals: monitoring, alerting, oncall, capacity planning, and incident response for systems with real user-facing impact

Requirements

• A Systems Thinker: capable of designing infrastructure that other teams (ML, feature teams, policy) build on top of, not just point solutions
• Experience building and evolving rules engines, workflow/decision systems, or similarly stateful business-logic services

Preferred

• Strong experience designing distributed systems: service APIs (RPC/gRPC), data modeling for high-throughput event ingestion, caching, and low-latency read paths

Pay

USD 196,750 - 243,290

• Comfortable with Ambiguity: this space is actively being redefined — you'll help set the standard, not just implement one handed to you
• 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