Sr. AI Lead Architect

Definity Insurance Company • Waterloo, ON

7d • Hybrid

About The Position

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.

Requirements

• Hands‑on experience architecting and operating AI or ML platforms at enterprise scale.
• Strong expertise with cloud‑native architectures, APIs, containerization, and scalable backend systems.
• Experience with at least one major cloud provider (GCP or AWS).
• Deep understanding of Model and artifact lifecycle management.
• Deep understanding of Continuous training, evaluation, and monitoring of AI systems.
• Deep understanding of Data access patterns, SDLC, MLOps/LLMOps guardrails, and operating models.
• Familiarity with GenAI tooling, orchestration frameworks, and LLM integration patterns.
• Strong technical communication and documentation skills.
• Pragmatic decision‑making with a strong risk‑awareness and ownership mindset.
• Collaborative team player capable of influencing across technology and business domains.
• Bachelor’s or Master’s degree in Computer Science, Technology, or a related discipline.
• 10+ years of combined experience in software engineering, data engineering, and AI/ML.
• Demonstrated experience architecting and operating production AI platforms at enterprise scale.
• Experience defining AI operating models, governance frameworks, and platform strategies.
• Hands‑on expertise with GCP or AWS required.

Nice To Haves

• Strong preference for cloud‑native AI platforms.
• Cloud certifications preferred.

Responsibilities

• 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).
• Standardize and evolve enterprise patterns for Prompt lifecycle management.
• Standardize and evolve enterprise patterns for Agentic workflows and tool orchestration.
• Standardize and evolve enterprise patterns for Model routing, fallback strategies, and cost optimization.
• Evaluate and recommend GenAI frameworks and tooling (e.g., LangChain, 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.
• Architect and evolve MLOps and LLMOps capabilities, including Prompt and model versioning.
• Architect and evolve MLOps and LLMOps capabilities, including Continuous evaluation and monitoring.
• Architect and evolve MLOps and LLMOps capabilities, including 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.

Benefits

• Hybrid work schedule for most roles
• Company share ownership program
• Incentive Program - Eligible employees may participate in various incentive plans which are paid out at the discretion of the company and subject to individual and company performance.
• Pension and savings programs, with company-matched RRSP contributions
• Paid volunteer days and company matching on charitable donations
• Educational resources, tuition assistance, and paid time off to study for exams
• Focus on inclusion with employee groups, support for gender affirmation surgery, access to BIPOC counsellors, access to programs for working parents
• Wellness and recognition programs
• Discounts on products and services

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 1-10 employees