Intelligence Engineer - Offline

Verisoul stops fake accounts and fraud in the era of AI. We distinguish real humans from bots and bad actors for high-growth companies like Clay, Augment Code, and Morning Consult .

6x YoY Growth: 6x ARR growth (to $2M) and scaled to 100+ customers.

Product Dominance: 80% competitive win rate; we catch 70-105% more fraud than legacy tools.

Strong Backing: Raised $8.8M Series A

Architect Reputation Systems: Build batch and nearline pipelines to score risk across identity attributes (email, phone, ISP) and lay the foundation for a scalable intelligence knowledge graph.

Deploy Graph Analytics: Use network science—including centrality, community detection, and embeddings—to detect synthetic accounts and visualize complex fraud clusters.

Develop Probabilistic Models: Engineer scoring algorithms that integrate historical reputation data and quantify uncertainty for dynamic entities like residential IPs.

Innovate & Mine Data: Conduct open-ended discovery on terabytes of historical data to invent new features and uncover evolving patterns in fraud network organization.

Experience: 4+ years as a full-stack engineer

Big Data Engineering: Experience with batch processing, data pipelines, and warehousing.

Entity Resolution: Understanding of how to link data points (email, IP, device) into a cohesive identity.

Mathematical Intuition: You understand probability, entropy, or graph theory and can apply them to messy real-world data.

Location: In-person in Austin, TX.

Engineering Team: To define the logic behind risk scores.

Platform Team: To make intelligence accessible via APIs.

In office 5 days a week in Austin, Texas!

All-in Optimism: Building a startup is hard. We bring the energy and steadfast optimism needed to push through challenges and accomplish the impossible—while having fun.

Total Ownership: Be a self-starter and a self-completer. Own high-impact problems end-to-end, combining structure with the execution skills to get the job done.

First Principles Curiosity: Challenge assumptions with a beginner’s mind. Rethink the "current way," test new hypotheses, and focus on finding the truth—even if it means changing your mind.