Senior Software Engineer - Detection

Description

Hypernative is the leader in real-time threat prevention for Web3, helping protocols, exchanges, and blockchain organizations detect and prevent exploits before they happen. Trusted by leading crypto-native companies, our platform protects billions of dollars in digital assets through advanced monitoring, threat detection, and automated response capabilities.

This role combines software engineering, data, and security. You'll build and own detection capabilities that identify malicious activity across blockchain networks, from research and design to production deployment and impact measurement.

We're looking for engineers who thrive on solving open ended problems and have experience building heuristics, detection systems, anomaly detection, scoring models, or other signal-driven solutions.

Responsibilities:

• Design and implement real-time detections for blockchain attacks and malicious activity
• Develop and back/forward test heuristics and detection logic
• Analyze large datasets to discover new detection opportunities
• Investigate incidents and translate learnings into scalable detections
• Build and maintain production detection modules and services
• Continuously measure, tune, and improve detection performance
• Partner with security researchers to operationalize new attack patterns

Requirements

• 5 years of developer experience in a large-scale production setting
• Experience building detections in cybersecurity/ fraud/ risk analytics or related domains
• Strong Python and SQL skills or comparable experience
• Experience designing heuristics, rules, scoring systems, or detection/anomaly/classification logic
• Strong analytical and data-driven problem-solving skills
• Experience/Familiarity with traditional Cyber Security Concepts
• Self-learner with a track record of independently driving projects from idea to production
• Familiarity with or curiosity about blockchain, cryptocurrency, and digital assets - advantage
• Experience applying machine learning to detection or risk problems - advantage