Compliance Engineer Intern

requirements. Support licensing and regulatory-readiness projects, including applicability research, gap analysis, evidence requests, policy review, and application-document preparation. Organize regulatory

requirements into structured modules, evidence categories, checklists, and mappings. Review AI outputs for factual consistency, source traceability, missing information, and formatting issues. Prepare initial drafts of compliance analyses, evidence guidance, client reports, pitch-deck content, and review materials. Support the maintenance of regulation-to-service mappings, evidence checklists, and submission-material reuse mappings. Organize customer-provided materials and identify potential evidence gaps for reviewer confirmation. Record reviewer feedback and update templates, evaluation cases, and compliance knowledge assets. Support coordination and request tracking across client-facing teams, compliance reviewers, and Engineering. Escalate unclear regulatory interpretations and unsupported conclusions to experienced reviewers.

Requirements Current enrollment in or recent graduation from a program in law, finance, accounting, risk management, public policy, business, computer science, or a related field. Strong research, analytical, and structured-writing skills. Strong attention to detail, particularly when reviewing regulatory sources, citations, and customer materials. Ability to organize complex information into clear checklists, summaries, presentations, and reports. Ability to manage multiple assignments and meet deadlines. Strong written and spoken English; professional Chinese proficiency is preferred but not required. Interest in digital-asset regulation, financial compliance, licensing, or AI-assisted compliance workflows. Familiarity with digital-asset regulation, VASP licensing, or similar regulatory frameworks is preferred. Previous internship, coursework, or project experience in compliance, law, audit, fintech, digital assets, or regulatory research is preferred. Basic understanding of LLM limitations, hallucination risk, source traceability, and human-in-the-loop review is preferred. \n This role must be performed outside the United States. We are unable to consider candidates who will work from within the U.S.

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