Описание

Leveraging LLM techniques to drive the development of next-generation on-chain risk identification and threat intelligence systems, including autonomous agent workflows capable of continuous monitoring, self-triggered investigation, and automated operational responses — reducing manual intervention across the full risk lifecycle from detection to resolution
Leading forensic investigations on real crypto theft, fraud, and market manipulation cases, integrating AI-assisted pattern recognition to accelerate root cause analysis
Researching post-quantum cryptographic algorithms (NIST PQC: ML-KEM, ML-DSA, SLH-DSA, FALCON) and their implications for blockchain security; assessing quantum computing threats to existing cryptographic foundations (ECDSA secp256k1, hash functions) and evaluating migration paths
Partnering with internal teams and external stakeholders for incident response, and engaging with academic institutions to translate frontier research into deployable security tools

You have a Master's or PhD's degree in Blockchain security, Computer Science, Data Science, or a related field
You are good at programming languages commonly used in blockchain analytics (e.g., SQL, Python, Javascript)
Experience applying machine learning or AI techniques to blockchain data analysis, fraud detection, or threat intelligence
A strong publication record in top-level industry or academic conferences is highly valued
You have experience with blockchain monitoring/forensic tools and analytics platforms
English is essential
You possess effective communication and collaboration abilities

Familiarity with NIST PQC standards (ML-KEM, ML-DSA, SLH-DSA, FALCON) and lattice/hash-based cryptography fundamentals is a plus
Understanding of quantum computing threats to elliptic curve cryptography and implications for key management in Web3
You have security or risk control experience as a plus
Proficiency in Mandarin can be an advantage

Blockchain Risk Control Lead