Sr. AI Lead Architect

Definity is the parent company to some of Canada’s most long-standing and innovative insurance brands, including Economical Insurance, Sonnet Insurance, Family Insurance Solutions, and Petline Insurance. Our ambition is to be one of Canada’s leading and most innovative property and casualty insurers. We can’t do that without our people, so we embrace and encourage a culture that’s collaborative, ambitious, rewarding, and empowering.

We offer a flexible, hybrid work experience where employees work from the office and virtually depending on the type of work they are doing and who they are working with. Bring your true self and be a part of our journey. It’s better here.

The AI Platform Architect is responsible for defining, evolving, and governing the enterprise AI platform. This role provides architectural leadership and deep technical expertise to enable scalable, secure, and operationally ready AI capabilities across the organization.

Working closely with technology, data, security, and business partners, the AI Platform Architect translates business requirements into reusable AI platform components, standards, and patterns. The role ensures GenAI capabilities are designed and operated in alignment with enterprise architecture, governance, risk management, and responsible AI principles, enabling multiple delivery teams to build AI solutions consistently and safely.

• Define and maintain the enterprise reference architecture for GenAI platforms, including LLM integration, orchestration, deployment, and evaluation patterns.
• Establish AI architectural standards, design patterns, and decision frameworks to enable consistent GenAI solution delivery.
• Partner with business, data, security, and engineering leaders to translate business needs into scalable, reusable AI platform capabilities.

• Design and guide implementation of GenAI systems combining non‑deterministic LLM inference with deterministic software, data, and workflow orchestration.
• Standardize and evolve enterprise patterns for:
  • Retrieval‑Augmented Generation (RAG)
  • Prompt lifecycle management
  • Agentic workflows and tool orchestration
  • Model routing, fallback strategies, and cost optimization
• Evaluate and recommend GenAI frameworks and tooling (e.g., Lang Chain, MCP, A2A, or equivalent).

• Define evaluation strategies and frameworks to measure GenAI quality across accuracy, relevance, safety, latency, and cost.
• Embed continuous evaluation, feedback loops, and monitoring into production AI workflows.
• Provide visibility into model performance through dashboards, metrics, and executive‑ready reporting.

• Architect and evolve MLOps and LLMOps capabilities, including:
  • CI/CD pipelines for AI workloads
  • Prompt and model versioning
  • Continuous evaluation and monitoring
  • Production observability (logs, traces, metrics, token usage, and cost)
• Ensure AI systems meet enterprise standards for reliability, scalability, and operational support.

• Integrate security, privacy, and compliance requirements into AI platform design.
• Apply responsible AI principles including guardrails, access controls, auditability, and risk mitigation.
• Ensure appropriate handling of personal and sensitive data across training, inference, and evaluation workflows.

• Build strong stakeholder relationships and lead executive‑level discussions on AI strategy and roadmap decisions.
• Translate AI platform strategy into well‑architected, end‑to‑end GenAI solutions aligned to business outcomes.
• Provide advisory support to delivery teams to accelerate adoption while maintaining architectural integrity.

• Support design reviews, production guidance, and platform troubleshooting for AI systems.

• Evaluate architectural trade‑offs across security, cost, scalability, and regulatory constraints.
• Adapt patterns and frameworks as GenAI technologies and business needs evolve.

• Design path‑finding AI platform solutions where precedent may be limited and outcomes…