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Senior AI Solutions Engineer

Toronto, Ontario, Canada

Interested in joining one of Canada’s top performing asset managers? CC&LFG is establishing an AI Enablement function to ensure artificial intelligence is adopted responsibly, securely, and at enterprise scale across the firm. The Senior AI Solutions Engineer is a foundational role in this function. This is not a product feature role and not a research role. You will act as a technical multiplier — designing reference architectures, building exemplar solutions, and enabling teams across the business to use AI safely and effectively. You will operate at the intersection of AI, data platforms, governance, and business workflows, balancing rapid experimentation with the rigor required in a regulated financial services environment. Success in this role is defined not by the number of models built, but by capability uplift, reuse, and sustainable adoption. Our offices operate on a hybrid model with three days in-office.  
Shape 
What You Will Do 
You will shape how AI is adopted at the enterprise level, not just what gets built. This role offers the opportunity to define standards, influence architecture, and enable meaningful AI-driven outcomes across investment, operations, and client-facing teams — while maintaining the trust, control, and discipline required in financial services.
 
AI Solution Design & Reference Implementations
  • Design and prototype AI-enabled workflows using LLMs, embeddings, RAG pipelines, and agent-based architectures.
  • Build reference implementations (not one-off solutions) that demonstrate approved patterns for:
    • Data access and grounding
    • Security and access control
    • Evaluation and monitoring
    • Human-in-the-loop oversight
  • Translate complex business problems into AI designs that are auditable, explainable, and operable.
Agentic AI Enablement
  • Design and operationalize agent-based patterns for workflow automation and decision support.
  • Define guardrails for agent autonomy, including escalation paths, confidence thresholds, and override mechanisms.
  • Partner with governance and risk teams to ensure agent behavior aligns with enterprise policies and regulatory expectations.
Platform & Data Alignment
  • Work closely with Data Platform and Architecture teams to ensure AI solutions align with:
    • Governed data products
    • Approved integration patterns (APIs, events, batch)
    • Platform constraints (Fabric, Databricks, cloud services)
  • Design AI solutions that assume imperfect enterprise data, not idealized datasets.
Enablement & Capability Building
  • Create reusable assets: templates, prompt libraries, evaluation harnesses, and onboarding guides.
  • Run enablement sessions, working labs, and design reviews to help teams adopt AI responsibly.
  • Act as a trusted technical advisor to business and technology leaders on when to use AI — and when not to.
Production Readiness & Lifecycle Management
  • Partner with platform teams to ensure AI solutions are production-ready:
    • CI/CD
    • Monitoring and alerting
    • Versioning and rollback
    • Cost awareness and controls
  • Continuously evaluate emerging tools and frameworks and recommend adoption only where they align with enterprise needs.
Cresting Success Shape 
  • Months 3-6:
    • Established trusted relationships with Data Platform, Security, Risk, and Architecture teams.
    • Delivered 2–3 reference AI patterns that teams actively reuse.
    • Defined baseline guardrails for agentic AI and LLM usage
  • Months 6-12:​
    • Multiple teams independently delivering AI solutions using enablement assets you created.
    • Reduced time-to-first-safe-AI-solution across the organization.
    • Clear, repeatable patterns for AI evaluation, deployment, and monitoring.
    • Leadership confidence that AI adoption is controlled, explainable, and scalable.
What You Bring 
  • Hands-on experience designing AI solutions using LLMs, embeddings, RAG, and agent frameworks.
  • Experience deploying AI solutions into real production environments, not just demos.
  • Strong familiarity with cloud AI platforms (Azure OpenAI, Azure ML, AWS Bedrock, OpenAI APIs).
  • Experience working in regulated or high-governance environments.
  • Strong understanding of data dependency, lineage, quality, and access control.
  • Ability to influence without authority and navigate ambiguity across teams.
  • Comfort balancing innovation with restraint, risk management, and operational discipline.
  • Clear communicator with technical and non-technical audiences.
  • Passionate about teaching, enabling, and building reusable capability.
  • Pragmatic: values solutions that are supportable, governable, and scalable.
The salary range for this position is $150,000 - $170,000.  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.  

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.  

 

 

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