AI Engineer
Posted 5hrs ago
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Job Description
AI Engineer building RAG and agentic AI systems for Legal and Compliance operations. Improving intelligent tools for Binance’s global cryptocurrency exchange and blockchain ecosystem.
Responsibilities:
- Work closely with Legal, Compliance, and the MLRO to support internal compliance policy reviews, files delivery, remediation tracking, and technical support
- Track compliance-related requirements for new product and service launches and coordinate action items with relevant stakeholders
- Partner with Legal and Compliance teams to identify, design, and implement AI-driven solutions that improve the efficiency and scalability of compliance and legal operations
- Enhance intelligent systems leveraging LLMs, RAG, agentic workflows, long-term memory, tool use, subagents, and multi-agent architectures for handling law files
- Develop benchmark frameworks and evaluation methodologies for legal and compliance AI systems, including benchmark dataset construction, annotation strategy design, and performance measurement
- Continuously evaluate and improve systems across retrieval quality, latency, groundedness, factuality, and task success metrics
- Conduct independent research and rapidly prototype new ideas to solve ambiguous legal and compliance workflow challenges
- Support related administrative and operational activities in accordance with company compliance requirements
Requirements:
- 5 years of relevant experience in compliance technology, legal technology, regulatory technology, or software/application development supporting compliance or legal functions
- Strong understanding of relevant compliance rules, regulations, and day-to-day compliance operations
- Bachelor’s degree required
- Background in AI, Computer Science, Engineering, Law, or related disciplines preferred
- Hands-on experience building production RAG systems, including embeddings, vector databases, hybrid search, reranking, chunking strategies, text preprocessing, and multimodal parsing
- Experience implementing advanced Agentic RAG approaches such as Self-RAG, Corrective RAG, adaptive retrieval, and multi-hop reasoning workflows
- Strong understanding of LLM and agent fundamentals, including prompt engineering, context engineering, memory, planning, tool use, MCP, and multi-agent systems
- Demonstrated ability to conduct independent research, solve ambiguous problems, and rapidly prototype practical solutions
- Strong written and verbal communication skills
- Bilingual English/Mandarin is preferred to be able to coordinate with overseas partners and stakeholders
Benefits:
- Competitive salary and company benefits
- Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
- Opportunities for career growth and continuous learning
- Flat organizational structure
- Autonomy in an innovative environment
- Equal opportunity employer



















