Data Analyst IV – CAD

Job Title: Data Analyst IV – CAD
Location: Toronto, ON (Hybrid)
Estimated Duration: 8 Months

Job Description
Description:
Senior GenAI Engineer (LLMs, RAG)
We are looking for a senior-level GenAI engineer to lead the development of a large language model assistant for insurance sales advisors. You will design GenAI pipelines, oversee model evaluation and prompt engineering, and partner with engineering teams to bring solutions into production.

Day-to-Day Responsibilities

• Architect LLM?based solutions (RAG pipelines, fine?tuning, embeddings, evaluation).
• Build scalable GenAI microservices and integrate with internal systems.
• Perform advanced prompt engineering, agent design, and safety guardrail development.
• Evaluate models (open?source and commercial) for performance, risk, and cost.
• Collaborate with data teams to prepare training data, knowledge bases, and analytics.
• Ensure compliance with insurance regulations and enterprise security frameworks.
• Mentor junior team members and establish best practices.
• Partner with business stakeholders to define problem statements, data requirements, and delivery approaches; document data sources and maintain templates.
• Oversee ongoing ingestion and refresh of knowledge bases and data pipelines supporting RAG; implement checks-and-balances and closed?loop measurement to improve solution quality over time.
• Present model performance, insights, and business impact to senior stakeholders; develop business cases and incorporate change?management considerations for successful adoption.
• Work with internal and external teams to productionize solutions and coach junior team members through delivery.

Qualifications

• 6+ years in machine learning, NLP, or AI engineering; 2+ years in GenAI/LLM work.
• Hands?on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, Llama, etc.).
• Strong expertise in RAG, vector databases, embeddings, and model evaluation methods.
• Proficiency in Python, data pipelines, and cloud?native architectures (Azure preferred).
• Experience deploying GenAI solutions in production environments.
• Understanding of insurance sales, underwriting, or financial services is an asset.
• Excellent problem?solving, communication, and cross?functional leadership skills.
• Bachelor’s degree in Computer Science, Math, Engineering, or equivalent practical experience.
• Strong SQL and data modeling skills; familiarity with relational and NoSQL stores (e.g., Hadoop/NoSQL) and BI/visualization tools (e.g., Power BI/Tableau) is an asset.
• Working knowledge of classical ML and statistical methods (e.g., regression, tree?based models, clustering) and of applying systematic, structured processes to operationalize analytics/LLM insights.
• Demonstrated ability to translate technical results into business language, manage stakeholder expectations, and support change management for solution rollout

Story Behind the Need – Business Group & Key Projects:
Can you please provide an overview of what a typical day in this role would look like, inclusive of any team members they’d be working with, structure, size, and day-to-day duties Typical Day

• Participate in the daily project update with the core team.
• Communicate with business & technical partners to confirm requirements and clarify timeline constraints.
• Propose and implement technical solutions based on business needs and project deadlines.
• Hands-on work with solution and architecture development tasks, validating the proposed results in POC format, but structuring.
• Sketch or draft Lucid Chart diagrams outlining proposed solutions to share with technical team.
• Log all tasks accurately and consistently in Jira.
• Collaborate closely with a project team of 2–3 members, plus the Data Infrastructure team, Web Backend and Web Front End Team.
• Mentor junior team members and establish best practices
• Report directly to the Project Team Lead.

Candidate Requirements
Must-Have Skills –

• LLMs (OpenAI, Azure OpenAI, Anthropic, Llama, etc.).
• RAG, vector databases, embeddings, and model evaluation methods
• Cloud?native architectures (Azure)
• Excellent problem?solving, communication
• Experience deploying GenAI solutions in production environments (MLOps – GENAI Ops)

Nice-to-have Skills—

• BI/visualization tools (e.g., Power BI/Tableau

Years of Experience: 6+ years in machine learning, NLP, or AI engineering; 2+ years in GenAI/LLM work
Degrees/Certifications Required: Bachelor’s degree in computer science, math, engineering, or equivalent practical experience.