AI Knowledge Management Lead

Northleaf Capital Partners•Toronto, ON

6d•Hybrid

About The Position

The AI Knowledge Management Lead will make Northleaf's trusted content and institutional knowledge usable for AI-enabled work. As a member of Northleaf’s AI Platform team, you will own the business content architecture and AI-readiness framework for Northleaf's governed knowledge estate, including priority content domains, taxonomy, metadata, source-of-truth rules, content ownership, access expectations, refresh standards and business-area onboarding. Northleaf is pursuing a business-led, platform-enabled AI model. This is a senior business-technical knowledge leadership role, not a cloud engineering or platform administration position. You will define content standards, readiness criteria and business validation of retrieval quality while partnering with M365, SharePoint, AI/search, data, privacy, security and records specialists on technical implementation and controls.

Requirements

12+ years of experience across knowledge management, information architecture, enterprise content management, enterprise search, digital workplace, document governance or related transformation roles.
Demonstrated experience designing and implementing taxonomies, metadata models, document ownership structures, content lifecycle processes, access/permission models, content standards and business stewardship practices.
Strong working knowledge of SharePoint content architecture and governance, including sites, libraries, permissions, metadata and content lifecycle; familiarity with Teams, Microsoft Search, Copilot, Purview, Power Platform, SharePoint Premium/Syntex or comparable knowledge and content-management capabilities is an asset.
Practical AI retrieval literacy, including how source quality, document structure, metadata, permissions, OCR/extraction, chunking, search relevance, grounding and citations affect AI-generated outputs.
Ability to partner credibly with platform and engineering specialists on Azure/Microsoft capabilities such as Microsoft Foundry, Azure AI Document Intelligence, Azure AI Search, Blob Storage, data connectors, document-processing pipelines and agent workflows. Hands-on AI or cloud engineering is not required, but the ability to define requirements and evaluate output quality is essential.
Experience working in a regulated, confidential and document-intensive environment; private markets, asset management, banking, pension, insurance, legal, professional services or consulting experience is strongly preferred.
Strong business-facing stakeholder management skills, with the ability to translate technical and information-management concepts into practical workflows for investment and corporate teams.
Excellent written and verbal communication skills, strong judgment, attention to detail and the ability to influence without direct authority in a collaborative, high-integrity environment.
University degree or equivalent experience in information management, library and information science, business, technology, data, knowledge management or a related field.

Nice To Haves

Familiarity with Teams, Microsoft Search, Copilot, Purview, Power Platform, SharePoint Premium/Syntex or comparable knowledge and content-management capabilities is an asset.
Hands-on AI or cloud engineering is not required, but the ability to define requirements and evaluate output quality is essential.

Responsibilities

Establish Northleaf's AI-ready knowledge and content architecture, including content domains, SharePoint site/library patterns, knowledge bases, taxonomy, metadata, document-readiness standards, source-of-truth rules, content ownership and refresh cadence.
Partner with front- and back-office business teams to identify, prepare and onboard priority content into protected AI-ready knowledge environments for search, agents and repeatable knowledge use.
Coordinate content tagging, clean-up, migration readiness and onboarding activities with business owners and platform teams so trusted document sets can support repeatable briefs, searches, reports and knowledge workflows across approved content.
Translate business workflows into AI-ready content and retrieval requirements, including source authority, source-of-truth and derivative-content rules, access expectations, sensitivity considerations, metadata requirements, citations, human review points and exception handling.
Partner with M365, SharePoint, Purview, AI/search, data and automation specialists on implementation patterns involving SharePoint Premium/Syntex, Microsoft 365 Copilot, Microsoft Foundry, Azure AI Document Intelligence, Azure AI Search, Blob Storage and related components as required.
Define business test cases and acceptance criteria to evaluate retrieval quality, search relevance, answer grounding, citation usefulness, source traceability and permissions safety; use feedback and quality measures to refine taxonomy and metadata.
Partner with AI data product, agent and automation leads to ensure document-based workflows, extracted-data outputs and reusable AI patterns are grounded in approved, well-structured content.
Support agents, document-processing flows and scheduled synthesis/reporting by defining the content requirements, source rules and quality checks needed for reusable workflow patterns.
Create repeatable playbooks, onboarding materials, ownership practices and office-hours support so business teams can progressively adopt content and knowledge standards without relying on one-off central support.
Track content-readiness progress, business-team onboarding, quality issues, backlog priorities, ownership gaps and foundation delivery milestones; communicate practical risks, dependencies and recommendations to leadership and partner teams.