Senior GenAI Engineer to to lead the development of LLM assistants for insurance sales advisors- 16341/16575

Senior GenAI Engineer to to lead the development of LLM assistants for insurance sales advisors- 16341/16575

Desired Location-Hybrid-Toronto- 3 days On Sita

Contract Duration: 04/07/2026- 12/31/2026

Hours: 37.5 Hours Per Week

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.
• 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 rollo

Nice to Have Skills

• Understanding of insurance sales, underwriting, or financial services is an asset.
• 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.

Education:

• Bachelor’s degree in Computer Science, Math, Engineering, or equivalent practical experience.