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Responsible AI & Data Governance Lead

LawZero

Job at a glance

Category
AI Governance
Work arrangement
On-site
Location
Montreal, Canada
Posted
Aug 31, 2026
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LawZero is hiring a Responsible AI & Data Governance Lead in Montreal, Canada. This is a AI Governance job in the governance, risk, and compliance field. Review the full details below and apply directly with LawZero.

Responsible AI & Data Governance Lead We are seeking a Responsible AI & Data Governance Lead to support in developing and implementing Law Zero’s data governance and responsible AI practices. The role is embedded within the Legal & Governance team but works closely with the research data product and evaluations team. Key Responsibilities: Data Governance Design and implement in collaboration with the Data and Legal teams LawZero’s data governance practices and policies including on sourcing and acquisition integrity inventory provenance and lineage licensing and IP and synthetic data governance.PII & Privacy Protection In collaboration with the Data and Legal teams develop and implement procedures for identifying redacting and securely handling Personally Identifiable Information in research datasets and product inputs. Responsible AI :& Monitor emerging AI governance frameworks develop and implement the adequate controls and processes. Embed ethics and responsible AI considerations in the product development lifecycle and applied use case projects. Research and Development Integrity Ensure research methodologies are documented to a standard that supports verification replication and audit maintain SOPs for publication open source releases and dataset sharing. Dual-Use & Bias Risk Management In collaboration with the Evaluations team conduct dual-use evaluations for research outputs with potential for harmful application coordinate comprehensive technical testing and safety evaluations including bias and fairness review and maintain documentation of testing methodologies and results for all research tools and products before external deployment. Internal AI Tool Governance Establish and manage policies and controls for the responsible deployment of third-party and internal AI tools for use by LawZero employees in coordination with the legal and IT teams. AI Policy Support the VP Legal & Governance and broader team in AI governance and policy initiatives.& ; & ; Skills and qualifications: & ; 5 to 7 years of experience in responsible AI data governance and/or technology legal/compliance roles. Technical literacy sufficient to understand AI/ML research methodologies data & training pipelines and AI product development and deployment. Demonstrated experience with data governance data provenance systems or AI governance in a technical context. Familiarity with AI governance frameworks including the EU AI Act NIST AI RMF ISO 42001 and Canada’s voluntary AI

Full responsibilities and requirements are on LawZero's application page.

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About LawZero
Hiring for governance, risk, and compliance jobs on GRC Careers.
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Location and market context

This job is based in Montreal, Canada on-site. Local candidates benefit from being close to LawZero's teams and regional hiring market. Confirm the exact in-office expectation and any relocation support with the employer.

About AI governance jobs

AI governance sits at the intersection of policy, risk, and engineering. Teams are standing up model inventories, use-case intake and review, risk classification, and control monitoring as regulation and board scrutiny of AI intensify. Jobs like this one are typically evaluated against frameworks such as NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices.

How to position yourself for this AI governance job

Strong candidates emphasize experience translating policy into operational controls, working across legal, compliance, security, product, and data teams, documenting AI system risks, and supporting governance processes. In your resume and outreach, tie your experience to how LawZero would apply NIST AI RMF, ISO/IEC 42001, the EU AI Act, and internal model-risk and privacy practices, and lead with concrete outcomes rather than duties.

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