Intelligence Engineer - Offline
Verisoul provides a fraud and fake-account detection platform for businesses. Its products detect duplicate accounts, bots, device fraud, proxy and VPN use, suspicious emails, and identity risks, serving customers across fintech, Web3, gaming, marketplaces, market research, and other online platforms.
Maintainer signals as of 8/23/2026
Funding history
Projects
About Verisoul
Verisoul offers a unified platform for preventing fake accounts and fraud through device fingerprinting, account linking, bot detection, email and phone intelligence, proxy and VPN detection, device-risk analysis, geolocation, identity checks, and facial matching. Its APIs, SDKs, dashboard, no-code rules, workflows, and AI fraud agents support real-time decisioning and fraud operations. The company serves online businesses and platforms, including fintech and payments companies, gaming and gambling platforms, marketplaces, social and community products, market research firms, advertising and media businesses, SaaS companies, and Web3 and crypto applications.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will analyze history, reputation, and patterns to catch sophisticated fraud that real-time checks miss. You will design batch and nearline pipelines, apply network science to detect synthetic accounts, engineer probabilistic scoring algorithms, mine terabytes of historical data, and collaborate with Engineering and Platform teams.
Requirements
- 4+ years as a full-stack engineer.
- Experience with batch processing, data pipelines, and data warehousing.
- Understanding of entity resolution linking email, IP, and device data into a cohesive identity.
- Understanding of probability, entropy, or graph theory applied to messy real-world data.
- In-person work in Austin, Texas.
Responsibilities
- Build batch and nearline pipelines to score risk across identity attributes such as email, phone, and ISP.
- Lay the foundation for a scalable intelligence knowledge graph.
- Use network science including centrality, community detection, and embeddings to detect synthetic accounts.
- Visualize complex fraud clusters.
- Engineer scoring algorithms using historical reputation data and quantify uncertainty for dynamic entities such as residential IPs.
- Conduct open-ended discovery on terabytes of historical data to invent new features.
- Uncover evolving patterns in fraud network organization.
- Collaborate with the Engineering team to define risk score logic.
- Collaborate with the Platform team to make intelligence accessible through APIs.
Benefits
- Free lunch
- $10K relocation bonus
- 100% insurance coverage
- 4% 401K match
- Unlimited vacation
- Up to 20 remote days annually
- Beautiful office
- 0.25%–0.5% equity grant