Regulatory Compliance Manager

About Bybit

Established in 2018, Bybit is a globally recognized cryptocurrency exchange and financial platform serving over 80 million users worldwide. It offers comprehensive digital financial services including trading, payments, wealth management, custody, and institutional support, integrating cutting-edge technology with a user-centric approach. The company prides itself on transparency, innovation, and building for the future of digital finance.

Role Overview

We are seeking a mid-level Regulatory Quant & Intelligence Specialist within our Regulatory Compliance department to develop AI-driven legal and compliance intelligence capabilities. This role blends regulatory expertise with quantitative analytical skills and AI workflow design to enhance regulatory decision-making and compliance automation. The successful candidate will model regulatory reasoning into structured systems, design AI-assisted compliance workflows, and ensure all processes remain transparent, auditable, and aligned with risk and regulatory standards.

Key Responsibilities

• Translate laws, regulations, and internal policies into structured decision frameworks, rule sets, and scoring models for embedding into compliance operations.
• Establish quantitative thresholds such as risk scores, confidence levels, and escalation triggers for determining appropriate automation versus human intervention.
• Develop prototypes of AI-powered workflows for regulatory research, licensing assessment, policy drafting, onboarding/KYC, surveillance, and incident management.
• Collaborate with engineering and data teams to implement large language model (LLM), retrieval-augmented generation (RAG), and agentic workflows that support compliance advisory and monitoring with thorough documentation and audit trails.
• Create and maintain quantitative models for assessing regulatory risks, scenario impacts, and enforcement implications to inform compliance strategies and licensing decisions.
• Design frameworks to evaluate and recalibrate decision models and AI workflows based on real cases, incidents, and regulator feedback.
• Conduct structured regulatory research across key jurisdictions including Singapore, EU/EEA, UK, Australia, and the Middle East, updating internal guidance accordingly.
• Translate regulatory changes into machine-readable rules and internal playbooks usable by compliance personnel and AI systems.
• Document decision frameworks, model assumptions, limitations, and human-in-loop controls according to AI governance and compliance best practices.
• Work closely with Legal, Product, and Engineering teams to integrate regulatory requirements into products and tools, and assist with regulatory and audit inquiries involving AI-based decisions.

Required Qualifications and Experience

• 3 to 5 years of experience in regulatory compliance, financial law, or similar roles within financial institutions, crypto/fintech, trading platforms, or regulatory bodies.
• Strong knowledge of financial services regulations, VASP licensing frameworks, and cross-border regulatory environments such as MAS, AUSTRAC, FCA, MiCAR, ADGM, or equivalent.
• Proficiency in constructing structured, tech-assisted legal/compliance workflows or internal tools using Python, scripting languages, or low/no-code platforms.
• Experience collaborating with or managing LLMs, APIs, workflow orchestration, and data/analytics tools, including prompt iteration and evaluation strategies.
• Exceptional analytical skills to formalize complex regulatory logic as clear models and guidance for humans and systems.
• Excellent communication skills to bridge Legal, Compliance, Engineering, and Product teams, explaining complex logic clearly to non-technical stakeholders and senior management.
• High levels of judgment, integrity, and accountability, with comfort working in dynamic, ambiguous regulatory environments typical of crypto and fintech sectors.

Personal Attributes

• A systems thinker and innovator who prefers building processes from first principles rather than incremental adjustments.
• Technically curious, open to experimenting with AI and emerging technologies within a compliant framework.
• Pragmatic and commercially minded, balancing risks, business goals, and operational realities when designing decision models.