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 Solutions Engineer, Agentic Automation

Reporting to Northleaf's AI Agent Lead, the AI Solutions Engineer will design, build, and deliver agentic AI and automation solutions for teams across Northleaf, translating business problems into working automations grounded in a practical understanding of how teams operate. You will help turn the firm's AI adoption and transformation priorities into solutions that are delivered, adopted, and trusted. This is a senior individual contributor role for a hands-on builder who combines business-process understanding with Microsoft low-code and AI engineering capability.

This is a hands-on, delivery-focused role with the opportunity to help shape and contribute to the firm's future enterprise agent ecosystem.



You will partner with business teams to understand their processes and pain points, then design, prototype, and build agentic solutions on the firm's low-code and AI platforms, extending solutions with code where it adds value.

Design and build agentic solutions:

Lead the hands-on design, development, and deployment of AI agents and automations across the firm's platforms, including Microsoft Copilot, Copilot Studio, Power Platform, and custom skills, tools, and integrations.

Deliver with consistency:

Progress solutions from quick prototype to tested, production-ready agents and workflows, maintaining a steady delivery cadence that provides business teams with tangible, working outcomes.

Analyze the business:

Work closely with teams across the firm to understand operations, map existing processes, and identify where agentic automation can deliver the greatest value.

Drive transformation:

Partner with business teams to rethink established processes, introduce AI-native approaches, and apply rapid prototyping to prove concepts and value.

Build toward an enterprise agent ecosystem:

Contribute to enterprise-scale, multi-agent solutions, including orchestration across agents, processes, and systems, in partnership with platform, security, and business stakeholders.

Develop reusable capability and patterns:





Convert individual solutions into reusable agent templates, skills, tools, and delivery patterns that accelerate future delivery and strengthen the firm's broader platform.

Qualifications Required

Approximately 8-12+ years of senior-level experience across automation, solution delivery, or related business-technology roles such as automation development, solutions engineering, technical consulting, AI delivery, or advanced business-application and Power Platform development.

Agentic AI and LLM-powered solutions: Practical experience building LLM-powered applications or agent-based systems, including agent and prompt design, knowledge bases and retrieval, evaluation and testing, and guardrails.

Platform expertise: Strong hands-on proficiency in several Microsoft stack capabilities, including Copilot Studio, M365 Copilot solutions, Power Platform, and Dataverse / SQL Server, with a low-code-first approach complemented by pro-code capability through APIs, system integrations, data management, and scripting in a language such as Python.

Business analysis and solution delivery: Ability to understand operations, map processes, identify automation opportunities, and progress practical solutions from prototype to adopted business capability.

Communication and stakeholder engagement: Ability to engage credibly with business and senior stakeholders and articulate technical concepts in business-appropriate language.

Preferred

Orchestration and multi-agent systems: Experience designing or implementing agent orchestration layers, including request routing, tool calling, workflow coordination, and memory and state management.

Agent skills and enterprise integration: Expe

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