Engineering Manager, Anti-Abuse & Security

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6 to 10+ years of engineering experience with 2+ years managing teams, ideally in anti-abuse, trust and safety engineering, fraud, or an adjacent adversarial domain.
A hands-on orientation: you still write code, review PRs, and prototype. Comfort using AI coding tools (Claude Code, Cursor, Replit Agent, or similar) as part of your daily workflow.
Experience building detection and enforcement systems at scale: rules engines, ML-based risk scoring, reputation systems, identity and device signals, or similar.
Experience with identity, KYC, or progressive verification systems is a significant plus. You've thought about how to layer trust signals and gate capabilities without wrecking conversion.
Strong product and metrics intuition. You've defined success metrics for ambiguous problems and built the data infrastructure to measure them.
Experience operating cross-functionally with Support, Legal, Security, and Growth teams. Comfort translating between technical detections and business impact.
Crisp written communication and the ability to build clarity in an ambiguous, 0-to-1 environment.

Experience with AI-native abuse vectors (prompt injection, LLM token farming, agent-driven abuse) or a track record of adapting quickly to novel threat categories.
Familiarity with payment fraud, card testing, coupon abuse, referral abuse, or promotional abuse.
Experience integrating KYC and identity verification providers (Prove, Persona, Socure, Stripe Identity, or similar).
Experience at a consumer platform, developer tool, or cloud provider with meaningful abuse surface area.
Background in security, trust and safety, or fraud prevention at a hypergrowth company.