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AI Knowledge & Governance Lead

Zafin
CompanyZafin
CategoryData & Analytics
LocationToronto
RemoteOn-site (inferred)
EmploymentNot stated
LevelLead
SalaryNot stated by the employer
Posted23 Jul 2026
Last verified6 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
Zafin is an AI platform company helping regulated institutions modernize how critical work is designed, governed, and delivered. Our technology enables organizations to move faster while maintaining the governance, accountability, and control required in highly regulated environments. Our portfolio includes Zafin AIOS , an agent orchestration platform for governed AI work; the Zafin Banking Platform , which helps banks modernize product, pricing, offers, billing, loyalty, and relationship management; and Zafin IO , an integration platform that connects data, systems, and workflows across complex enterprise environments. Headquartered in Toronto, Canada, Zafin partners with leading financial institutions across North America, Europe, the Middle East, Africa, and Asia-Pacific. As AI transforms the future of financial services, we're building the platforms that help regulated organizations adopt AI responsibly and at scale. What’s the Opportunity?   The AI Knowledge & Governance leader is a strategic leadership role responsible for establishing the knowledge, governance, trust, and compliance capabilities that underpin Zafin’s AI Operating System (AIOS). The position ensures AI solutions are built on trusted knowledge, governed by enterprise standards, and operated safely, transparently, and in compliance with regulatory expectations, enabling clients to confidently adopt AI within regulated environments. This role also establishes and evolves the governance, risk, compliance, evaluation, and responsible AI frameworks that enable AIOS to operate securely and responsibly across enterprise environments. The role owns the AI Knowledge and Governance pillars of the AIOS model: defining enterprise standards for knowledge lifecycle management. For example, capture, curation, publication, and reuse of knowledge on one side; evaluation, security, auditability, operating controls, and regulatory compliance on the other. These capabilities ensure AI solutions remain trusted, explainable, reusable, and production-ready across all Functional Delivery Units (FDUs). The role also defines evaluation and compliance standards that all FDUs must satisfy before production deployment and owns the audit and monitoring framework governing AI agent behavior, safety, and regulatory compliance across the platform. This role also defines the governance metrics, operating reviews, assurance mechanisms and participates in cadenced forums to continuously monitor AI quality, risk, compliance, and knowledge maturity across the platform. The outputs feed directly into the AI agent quality and risk layer of the platform's metrics framework, including escaped defect rate, architecture compliance, and security gate pass rate to name a few.  The role serves as the primary point of accountability for AI knowledge and governance with client engagement(s), partnering with client risk, compliance, legal, audit, and technology leaders to ensure AIOS aligns with client governance requirements and any emerging AI regulatory expectations. What Will You Do?   Define enterprise evaluation, risk, compliance, and responsible AI standards required of FDUs prior to production deployment of AI solutions. Own the enterprise audit, monitoring and governance framework governing AI behaviour, safety, explainability, regulatory compliance, and operational performance across AIOS. Lead the integration of knowledge and governance controls across all squads to embed evaluation and governance controls into delivery from design through production Partner with client risk, compliance, and audit functions to validate that the platform meets banking regulatory requirements (e.g., Model Risk Management, AI governance frameworks). Serve as the primary advisor to client risk and compliance teams on AI governance. Identify and prioritize AI risk and governance investments; justify business cases for control enhancements or new capabilitie