AI Knowledge & Governance Lead

Zafin•Toronto, ON

1d•Hybrid

About The Position

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.

Requirements

10-15+ years of progressive experience in AI governance, knowledge management, data governance, risk and compliance, or related fields, scaled to level including leadership responsibility across multiple teams or initiatives.
Degree in Comp Sci, Library/Information Science, Business, or related field, or equivalent experience.
Experience defining enterprise knowledge management, taxonomy, metadata tagging, and content governance strategies that enable trusted AI systems.
Experience with enterprise knowledge platforms, documentation governance, content lifecycle management, and AI knowledge repositories.
Deep understanding of how knowledge quality, governance, and life cycle management influence or affects AI performance, explainability, and trustworthiness
Deep knowledge of AI risk frameworks, model governance practices, and regulatory compliance requirements relevant to financial services (Basel III, Model Risk Management guidance, emerging AI regulations).
Demonstrated experience designing and implementing evaluation methodologies, monitoring systems, and auditability controls for AI/ML systems in production.
Strong understanding of data governance and knowledge management practices, particularly for ensuring data quality and regulatory compliance.
High attention to detail and demonstrated comfort operating in regulated, audit-driven environments with strong control requirements.
Excellent ability to communicate technical AI risk and governance concepts clearly to both non-technical and executive stakeholders.
Strong analytical capabilities with the ability to translate complex business, regulatory, and operational knowledge into AI knowledge assets and standards.
Working understanding of enterprise data architecture and integration patterns as they relate to knowledge and content systems.

Nice To Haves

Familiarity with banking processes and policy frameworks.
Experience supporting an audit or regulatory examination involving AI or automated decision-making.
Experience leading enterprise AI governance, model risk, responsible AI, or enterprise risk functions in regulatory industries and/or enterprise software organizations.
Track record of building governance frameworks and audit systems that scaled across organizations.
Regulatory examination experience or direct interaction with banking regulators (Federal Reserve, OCC, FDIC, etc.).
Expertise in specific banking regulatory frameworks (e.g., SR 11-7, SR 21-1, Model Risk Management) or emerging AI governance standards to enterprise AI solutions.
Published thought leadership / contributions or speaking engagements on AI governance, responsible AI, or risk management in AI systems.

Responsibilities

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 capabilities.
Communicate AI risk, compliance status, and governance decisions to executive stakeholders, clients, and regulators quarterly or as needed.
Own the lifecycle for AI knowledge assets, including capture, curation, publication, governance, reuse, and retirement across client engagements.
Define enterprise standards governing AI knowledge quality, taxonomy, ownership, lifecycle management, and reuse; all of which underpins AI agent accuracy and reliability.
Ensure governance evidence, audit trails, policy documentation, and regulatory artifacts are maintained to support enterprise assurance and client confidence.
Develop evaluation specialists, governance practitioners, and future leaders while building enterprise capability in AI governance and responsible AI practices.
Define and evolve the enterprise AI governance operating model, ensuring governance practices scale consistently across Product, Customer Enablement teams.
Chair enterprise AI governance forums and provide recommendations on AI risk acceptance, policy exceptions, etc.