Senior Software Engineer- User Behavior

What you'll do

• Build a low-latency behavioral data layer and centralized consequence engine combining rules and ML risk signals.
• Develop a unified framework for safety interventions and abuse reporting, including LLM-based classification and agentic review workflows.
• Own end-to-end delivery and operation of reliable, explainable serving infrastructure, from design through migration and production support.

What they ask for

• 5+ years building and operating production backend systems at scale, ideally in Go or a comparable statically-typed backend language.
• Strong distributed-systems experience, including service APIs (RPC/gRPC), high-throughput event ingestion, caching, and low-latency read paths.
• Experience with 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 production operations fundamentals.

Nice to have

• Trust & Safety, fraud, risk, or other adversarial-domain experience.
• Feature stores or ML-serving infrastructure; backend-driven UI frameworks.

Pay

$196,750 — $243,290 USD (base salary)

Tools

Go, RPC/gRPC, LLM

AI focus

Combine ML risk signals with deterministic rules for safety decisions; use LLM-based classification, agentic review workflows, and ML models to improve abuse-report routing, prioritization, and reporter feedback.