Related skills
sql python kafka spark rag📋 Description
- Design “Sherlock”-style autonomous agents to investigate suspicious fraud activity
- Build reasoning-capable agents that analyze user behavior, device fingerprints, and trading history to assess withdrawals
- Develop market manipulation detection agents that analyze unstructured social sentiment alongside order book data
- Identify pump-and-dump schemes and wash trading
- Build LLM-based triage systems to handle high volumes of risk alerts
- Use agents to pre-screen alerts by analyzing alert context and historical false positives
🎯 Requirements
- LLM application experience: 2+ years building apps with GPT, Claude, or open-source LLMs
- Agent frameworks: LangGraph, LangChain, or CrewAI
- RAG for domain knowledge: Retrieval systems that fetch relevant contextual information
- Evaluation: Design evaluation sets to measure agent performance
- Python mastery: Write production-ready, maintainable code
- Data engineering: SQL and data pipelines (Kafka, Spark)
- Crypto familiarity: On-chain analysis, DeFi concepts, wallet addresses
- Domain interest: Trust & Safety, anti-fraud, or financial risk domains
🎁 Benefits
- Work-from-home arrangement
- Competitive salary and company benefits
- Equal opportunity employer
- Career growth and continuous learning
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