AI Knowledge Management Lead

About Northleaf Capital Partners  Northleaf is a global private markets investment firm focused on mid-market companies and assets. With US $31 billion in capital commitments raised to date, Northleaf has an established, long-term track record as an investor in private equity, private credit and infrastructure globally.
Northleaf’s 300+ person team, located in Toronto, Chicago, London, Los Angeles, Melbourne, Menlo Park, Montreal, New York, Seoul and Tokyo, is focused exclusively on sourcing, evaluating and managing private markets investments. Northleaf manages closed and open-end funds across a range of global private markets strategies and a series of separately managed accounts with customized investment strategies tailored to meet the specific needs of leading institutional investors and family offices.

As part of its ambitious growth strategy, Northleaf is also developing specific private markets products and investment solutions for insurance and wealth management clients.
Position: AI Knowledge Management Lead  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, where 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.

Key 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 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.
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