Staff Engineer, Fraud & Abuse

Job not on LinkedIn

🕒 October 29

🦬 Wyoming – Remote

🦬 Wyoming – Remote

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

👻 Ghost score 0%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Venice.ai

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2024

🤖 Artificial Intelligence

☁️ SaaS

🔌 API

🔥 Funding within the last year

💰 $65M Series A on 2026-06

Artificial Intelligence • SaaS • API

Venice. ai is a privacy-focused AI platform that provides access to leading third-party and open-source models for generating text, images, video, audio, code, embeddings, and agents. The company emphasizes user privacy through anonymized access, zero data retention for self-hosted models, Trusted Execution Environments (TEEs), and client-side end-to-end encryption. Venice offers a unified API compatible with OpenAI and agent stacks, developer tools (SDKs, LangChain, OpenAI SDK compatibility), and products for creators and enterprises with tiered pricing plans. Its features include multimodal generation, image and video creation/editing/upscaling, text-to-speech and music generation, and support for uncensored models.

📋 Description

• Build detection systems from scratch, including rules engines, anomaly detection, and behavioral signals • Work across TypeScript, Rust, and Python as needed • Investigate fraud spikes and new abuse patterns hands-on and ship fixes • Partner with the payments team to build fraud controls into payment flows • Stop automated abuse such as bot-driven fake signups, rate-limit evasion, token farming, and API key abuse • Prevent account takeover through detection and friction for credential stuffing, session hijacking, and account-sharing rings • Tune detection thresholds, measure impact, and minimize false positives

🎯 Requirements

• 10+ years of software engineering experience, with strong security fundamentals • Comfortable across TypeScript, Rust, and Python • Self-directed and comfortable with ambiguity • Pragmatic about tooling; able to recommend, evaluate, and choose a fraud and abuse stack • Incident response mindset • Experience with payment fraud detection, chargeback management, or billing abuse • Familiarity with Cloudflare, WAF rules, bot management, or similar edge-layer controls • Prior experience building trust & safety or fraud detection systems at a consumer-facing platform • Experience with ML-based anomaly detection or behavioral analytics

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