Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field
Proven experience working with on-chain data and a strong understanding of blockchain transaction structures
Expertise in transformer models (e.g., BERT, GPT) and their practical applications
Experience with graph databases (e.g., Neo4j, Amazon Neptune) and graph query languages (e.g., Cypher, Gremlin)
Hands-on experience building AI agents, preferably using LangGraph or equivalent frameworks
Demonstrated success in deploying AI/ML models and services in production environments (e.g., via REST APIs, microservices, or cloud platforms)
Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face)
Familiarity with blockchain ecosystems and smart contract mechanics
Knowledge of AI techniques in anomaly detection
Experience with scalable data pipelines and cloud infrastructure (e.g., AWS, GCP)
Strong problem-solving abilities and critical thinking skills in fraud detection scenarios
Excellent communication skills and ability to work in a collaborative, cross-functional environment