AI Solutions Engineer

Connor, Clark & Lunn Financial Group Ltd.; Toronto; On-site; CAD 125,000 - 145,000; Full time

Job summary

Connor, Clark & Lunn Financial Group is hiring an AI Solution Engineer to build end-to-end AI assistants, agents, and workflows from signed specifications. You will own retrieval pipelines, prompt logic, tool integrations, and production quality, collaborating with Data Engineering and MLOps to ship responsibly in a regulated financial services environment.

This hybrid role requires in-office presence three days weekly in Canada.

Qualifications

• 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).
• Experience with agent frameworks (LangChain, LlamaIndex or equivalents), including tool use, orchestration, and multi-step flows.
• Experience on enterprise AI platforms (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) and translating into retrieval-ready assets.
• Delivery mindset and strong written communication, hold scope, write clear technical documentation, and finish to production-quality.

Responsibilities

• 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 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.

Skills

Python

LLM applications

RAG

LangChain

LlamaIndex

Data extraction and processing

Tools

LangChain

LlamaIndex

Azure OpenAI

Google Vertex AI

Anthropic APIs

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 an d MLO ps to ship responsibly in a regulated financial services environment. Weoperateon a hybridmodel withthree days a week in-office tofacilitateteam 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 wher e appropri ate , an d mainta in clean, reviewable documentation
• Partner with Data Engineering to make data retrieval-read y, 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.

For a closer look at how you can build your career with us, we invite you to explore cclgroup.com .

CC&L Financial Group is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to gender, ethnicity, religion, sexual orientation or expression, disability, or age.

Your application will be reviewed by a member of the hiring team - AI is not used in the screening, assessment or selection of applications at this time.