Connor, Clark & Lunn Private Capital Ltd.

Financial Services

AISolutionsEngineer

CA$125–145k Toronto, Ontario, Canada FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“AI Solutions Engineer at Connor, Clark & Lunn Private Capital Ltd. . Skills: Generative AI, Large language models, Agent-based workflows, Prompt engineering. Understand processes. Understand pain points”

What You'll Achieve.

Improve advisor experience; Improve client experience; Make information easier to find; Make information easier to use; Reduce manual servicing work; Reduce operations work; Strengthen consistency; Strengthen controls; Strengthen governance

Industry & Context.

Financial Services
Problems you'll solve

Problem-solving skills; Translate business needs; Solve workflow problems

What They're Looking For.

Must Have

3-5+ years experience, Python skills, Hands-on RAG experience, Experience with agent frameworks, Experience on enterprise AI platforms, Prompt engineering fundamentals, Comfort working with data, Bachelor's degree or equivalent experience

Nice to Have

Experience in financial services, Experience in wealth management, Experience in asset management, Experience in banking, Experience in insurance, Experience in fintech, Experience in consulting, Experience with Salesforce, Experience with Agentforce, Connecting Salesforce with AI platforms

What You'll Do.

Understand pain points

Understand data sources

Understand user needs

Translate business requirements

Collaborate across teams

Design AI-enabled tools

Build AI-enabled tools

Configure AI-enabled tools

Use structured outputs

Document solution designs

Document operating procedures

Support transition prototypes

Build practical tools

Solve workflow problems

Learn how business works

Move ideas to solution

How You'll Work.

Team & Collaboration

Work with business teams; Collaborate across Private Capital; Collaborate across Technology; Collaborate across Data; Collaborate across Risk; Collaborate across Compliance; Collaborate with business teams; Collaborate with technical teams

Communication Scope

Explain technical concepts

Process & Methodology

Prototype to scalable solution

Full Job Description

Interested in joining one of Canada’s top performing asset managers? We are looking for an AI Solutions Engineer for a new full-time position on our Connor, Clark & Lunn Private Capital team. In this role, you will design, build, test and improve practical AI-enabled tools and workflows that help Private Capital teams better serve high-net-worth clients, advisors and internal stakeholders. Our use cases are focused on real business value: improving the advisor and client experience, making information easier to find and use, reducing manual servicing and operations work, and strengthening consistency, controls and governance across complex processes. This is a hands-on role focused on generative AI, large language models and agent-based workflows. You will work closely with Private Capital, Technology, Data, Risk and Compliance to turn business needs into secure, useful and well-governed solutions that support areas such as sales, client servicing, documentation, reporting, approvals and compliance. If you enjoy building practical tools, solving workflow problems, learning how a business works, and moving ideas from prototype to scalable solution, this could be a great opportunity. Our offices operate on a hybrid model with three days a week in-office. What You Will Do Work with business teams to understand processes, pain points, data sources and user needs. Translate business requirements into practical solution designs, including user flows, prompts, data inputs, retrieval approaches, review steps and success measures. Collaborate across Private Capital, Technology, Data, Risk, and Compliance to deliver secure, practical and well-governed AI solutions. Design, build, and configure AI-enabled tools, assistants, agents, and workflow automation. Connect AI solutions to relevant business systems, documents, internal knowledge sources, and APIs where appropriate. Use techniques such as prompt design, retrieval-augmented generation, structured outputs, tool calling, ev

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