AI Solutions Engineer

Connor, Clark & Lunn Financial Group Ltd.

$125K — $145K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Strong Python skills, especially with LLM applications.
  • Hands-on experience with RAG, document processing, and retrieval evaluation.
  • Familiarity with agent frameworks like LangChain or LlamaIndex.
  • Experience on enterprise AI platforms (Azure, Google Vertex AI).
  • Knowledge of prompt engineering fundamentals and structured prompting.
  • Comfortable working with semi-structured and unstructured data.
  • Strong communication and technical documentation skills.

Responsibilities

  • Build AI assistants and agents end-to-end from specifications.
  • Design and maintain retrieval pipelines and access controls.
  • Engineer and test prompts; document failure modes and edge cases.
  • Ensure code quality and maintain clean documentation.
  • Collaborate with Data Engineering to prepare data for retrieval.
  • Deploy AI solutions via MLOps pipelines, ensuring monitoring and rollback readiness.
  • Work with affiliate teams to gather feedback and integrate changes.

Benefits

  • Hybrid work model with three days in-office for collaboration.
  • Opportunity to work on cutting-edge AI solutions in finance.
  • Engage with a high-performing team in a respected organization.
  • Access to performance bonuses as part of the compensation package.
  • Support and resources for professional growth and career development.
Full Job Description
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.

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