About this role

▸about Binance — company background

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

We are seeking a highly motivated and technically strong professional to support the intersection of Compliance, Legal, and AI-driven technology innovation. This role will work closely with the **Legal team, MLRO, Compliance, and cross-functional stakeholders** to enhance internal compliance processes, support policy and audit-related initiatives, and design intelligent systems that improve the efficiency and scalability of compliance and legal operations.

The ideal candidate combines practical compliance or legal-tech experience with hands-on expertise in LLMs, RAG systems, and agentic AI architecture. This person should be comfortable operating in ambiguous environments, translating business and regulatory needs into technical solutions, and rapidly prototyping and deploying AI-native tools.

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.

Used the 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.