Interested in joining one of Canada’s top-performing asset managers? We’re hiring an AI Solution Engineer in our AI Solutions engineering team. You build the AI systems that Connor, Clark & Lunn Financial Group and our affiliate teams use in day-to-day work. You turn signed-off specifications into production-ready AI assistants, agents, and workflow automations. You own build quality, reliability, safety, traceability, and maintainability, and partner closely with Data Engineering and MLOps to ship responsibly in a regulated financial services environment. We operate on a hybrid model with three days a week in-office to facilitate team collaboration.
What You Will Do
- Build AI assistants and agents end-to-end from a signed-off spec, retrieval, tool integrations, prompt logic, source citation, and workflow integration
- Design and maintain retrieval pipelines, chunking strategy, metadata schema, indexing, access controls, and query optimization
- Engineer prompts with discipline, write, test, evaluate, and iterate; document failure modes and edge cases
- Own code quality and handoff, version artifacts, write tests where appropriate, and maintain clean, reviewable documentation
- Partner with Data Engineering to make data retrieval-ready, define ingestion needs, document assumptions, and validate data quality impacts
- Deploy through standard MLOps pipelines, monitoring/alerting, rollback readiness, cost controls, and operational runbooks
- Collaborate with affiliate teams during builds, demo real increments, capture feedback, and incorporate changes without breaking scope
- Document known limitations, risks, and mitigations before UAT, set expectations and prevent surprises for business stakeholders
What You Will Bring
- Strong Python skills with experience shipping LLM applications end-to-end (build, test, deploy, and operate)
- Hands-on RAG experience, document processing, vector databases/search, and retrieval evaluation (precision/recall, grounding quality)
- Experience with agent frameworks (e.g., LangChain, LlamaIndex or equivalents), including tool use, orchestration, and multi-step flows
- Experience on enterprise AI platforms (e.g., Azure OpenAI, Google Vertex AI, Anthropic APIs), including security and cost/performance trade-offs
- Prompt engineering fundamentals, structured prompting, output constraints, adversarial/failure-mode testing, and reproducibility
- Comfort working with semi-structured/unstructured data (PDFs, financial docs, emails, notes) and translating it into retrieval-ready assets
- Delivery mindset and strong written communication, hold scope, write clear technical documentation, and finish to production-quality
The salary range for this position is $125,000 - $145,000. The salary range provided reflects the base salary range for this position as required by legislation. In addition, there is an annual performance bonus which contributes to the total compensation for this position. Further questions may be directed to the HR team during the interview process.
#LI-Hybrid #LI-KC1
For a closer look at how you can build your career with us, we invite you to explore cclgroup.com.
We are committed to providing an inclusive, accessible recruitment and selection process. We welcome and encourage applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process. Please contact [email protected] if you require accommodation.
AI may be used to support certain stages of our screening & recruitment process. These tools support, but do not replace, human judgment and decision-making.
Skills Required
- Strong Python skills and experience shipping LLM applications end-to-end, including building, testing, deploying, and operating them.
- Hands-on experience with RAG, document processing, vector databases or search, and retrieval evaluation.
- Experience with agent frameworks such as LangChain, LlamaIndex, or equivalent, including tool use, orchestration, and multi-step flows.
- Experience with enterprise AI platforms such as Azure OpenAI, Google Vertex AI, or Anthropic APIs.
- Knowledge of prompt engineering, structured prompting, output constraints, adversarial testing, failure-mode testing, and reproducibility.
- Comfort working with semi-structured and unstructured data, including PDFs, financial documents, emails, and notes.
- Strong written communication, technical documentation, scope management, and delivery focus.
What We Do
Connor, Clark & Lunn Financial Group is a Canadian privately owned and employee-owned asset management firm. Through a multi-boutique platform and affiliated investment teams, it provides traditional and alternative investment products and services to individuals, institutional investors, and advisors. The firm offers strategies including equities and fixed income, operating across Canada, the United States, the United Kingdom, and India. Its entrepreneurial structure supports innovation and scalable investment solutions for clients worldwide.
