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Urban Ridge Supplies

AI Solutions Engineer

Toronto, ON, Canada

Pay: The salary range for this position is $125,000 - $145,000.
Job type: Full-time
Posting language: English
Posted: Sep 24, 2026

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Original 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.

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 talentacquisition@cclgroup.com 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.

Job Id: z/gU2UW5CP8i9Pe0+u8GDSrAAQY2qKPQz1iZtofgHGy8cjA3lpHwfw0tiXX/xxE8fpZNq8sFXmttS0gPakN2qe+9UXDxXMI+Gg==

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More about this job

Responsibilities

Build and operate production-ready AI assistants, agents, retrieval pipelines, and workflow automations, ensuring quality, reliability, safety, traceability, and maintainability. Collaborate with data, MLOps, and affiliate teams to deploy solutions responsibly, incorporate feedback, and document risks, limitations, and operational procedures.

Requirements

Requires strong Python skills and experience delivering LLM applications end-to-end, including hands-on RAG, document processing, vector search, retrieval evaluation, and agent frameworks. Candidates should also have experience with enterprise AI platforms, disciplined prompt engineering and failure testing, unstructured data, and production-quality delivery and documentation.

Skills

Python
LLM Application Development
Retrieval-Augmented Generation
Document Processing
Vector Databases
Retrieval Evaluation
Agent Frameworks
Tool Integration
Prompt Engineering
Enterprise AI Platforms
Data Retrieval
MLOps
Testing and Evaluation
Technical Documentation
Workflow Automation
Data Quality Validation

Visa sponsorship

Not detected in the job text

Keywords

Python
LLM Applications
Retrieval-Augmented Generation
RAG
AI Assistants
AI Agents
Workflow Automation
Retrieval Pipelines
Chunking Strategy
Metadata Schema
Indexing
Access Controls
Vector Databases
Retrieval Evaluation
LangChain
LlamaIndex
Azure OpenAI
Google Vertex AI
Anthropic APIs
Prompt Engineering
Tool Orchestration
Document Processing
MLOps
Data Engineering
Monitoring and Alerting
Rollback Readiness
Cost Controls
Financial Services
UAT
Data Quality

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