The Director, Solution Architecture for Agentic AI and Corporate Systems reports to the Assistant Vice President for Corporate Enterprise Architecture and leads solution architecture for complex, high impact initiatives across business groups. 

This role ensures that solution designs are aligned with enterprise architecture standards, business strategy, and technology roadmaps while enabling efficient, high quality delivery. The Director acts as a senior technical and architectural advisor, balancing strategic direction with practical execution guidance and continuously improving solution architecture practices. 

The initial focus of this role will be solution architecture leadership for Agentic AI and Generative AI-enabled initiatives, with support for additional Corporate IT initiatives as priorities evolve. 

Qualifications 

Education 

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Business Technology, or a related discipline, or equivalent practical experience. 

• Master’s degree is an asset. 

• Architecture certifications such as TOGAF, IASA, AWS Certified Solutions Architect, or equivalent are preferred. 

• Relevant cloud and AI credentials are valued, such as AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer - Associate, Azure AI Engineer, or equivalent credentials. 

Experience 

• 10 or more years of progressive experience in solution, enterprise, platform, application, integration, or domain architecture roles. 

• Demonstrated experience leading architecture for large scale, complex technology initiatives in a regulated enterprise environment. 

• Strong hands-on technical understanding of application, integration, data, security, cloud, operational, and AI-enabled solution architecture. 

• Experience guiding delivery teams through architecture governance, design reviews, risk assessments, decision records, exception management, and production readiness activities. 

• Solid applied understanding of Generative AI and Agentic AI patterns, including LLM-enabled applications, RAG, tool using agents, supervised workflows, human approval patterns, and AI governance considerations. 

• Experience designing, evaluating, or providing architecture guidance for cloud based AI, automation, or data driven solution capabilities, preferably in the AWS ecosystem or equivalent cloud platforms. 

• Experience partnering with Security, Data, Privacy, Risk, Legal, Operations, and business stakeholders to deliver secure, compliant, production ready solutions. 

• Experience evaluating build vs buy decisions, including SaaS embedded AI, enterprise AI platforms, vendor capabilities, cost, integration complexity, and long term sustainability. 

Preferred Experience and Assets 

• Financial services, insurance, or other regulated industry experience. 

• Exposure to Responsible AI, model risk management, third party risk, technology and cyber risk, privacy, data governance, and regulatory expectations relevant to AI-enabled solutions. 

• Experience with AWS AI services such as Amazon Bedrock, Amazon Bedrock Agents, Amazon AgentCore, model hosting, retrieval, orchestration, observability, or equivalent AI platform capabilities. 

• Practical experience with agent orchestration frameworks or patterns such as LangGraph, Semantic Kernel, Strands, AutoGen, or similar technologies. 

• Understanding of LLMOps, MLOps, AgentOps, AI evaluation, prompt and configuration management, AI monitoring, and production support models.

• Experience assessing AI capabilities in enterprise platforms such as ServiceNow, Salesforce, Microsoft, Workday, SAP, Oracle, or similar SaaS, ERP, and COTS environments. 

• Experience with data science or ML engineering tools such as TensorFlow or PyTorch is an asset but not required. 

Main Accountabilities 

• Lead end-to-end solution architecture for complex, high impact Corporate Systems initiatives, with an initial focus on Agentic AI, Generative AI, AI-enabled workflow automation, and related enterprise platform capabilities. 

• Translate business strategies, objectives, and requirements into secure, scalable, resilient, and cost effective solution architectures aligned with enterprise standards, business priorities, and technology roadmaps. 

• Guide business and delivery teams in selecting the right solution pattern, including when to use Agentic AI, Generative AI, embedded platform AI, workflow automation, traditional integration, or other enterprise technology approaches. 

• Lead solution design across application, integration, data, security, cloud, operations, AI, and nonfunctional requirements, including performance, scalability, resilience, observability, auditability, maintainability, and cost. 

• Define, apply, and evolve reusable architecture patterns and guardrails for AI-enabled and Corporate Systems solutions, including model access, context management, data sourcing, tool invocation, human oversight, audit evidence, and operational support. 

• Assess architectural trade-offs, risks, dependencies, technical debt, vendor constraints, build vs buy options, integration complexity, data control, security, privacy, compliance, and long term sustainability. 

• Partner with Enterprise Architects, Domain Architects, Business Architects, AI platform teams, Cybersecurity, Data, Risk, Legal, Privacy, Operations, delivery teams, vendors, and business stakeholders to drive alignment and accountable outcomes. 

• Provide architecture governance support, including design reviews, risk assessments, exception management, architecture decision records, AI solution reviews, and production readiness assessments. 

• Establish and maintain architecture runway artifacts such as conceptual designs, target state architectures, transition designs, reusable patterns, solution guardrails, decision records, and production readiness guidance. 

• Coach architects, engineers, and delivery teams on pragmatic solution design, enterprise standards, responsible AI adoption, reuse, modernization, and effective delivery practices. 

Skills & Competencies

• Leads architecture for complex initiatives and balances business outcomes, enterprise standards, delivery realities, and long term maintainability. 

• Understands how Generative AI and Agentic AI affect solution design, including context, retrieval, model access, tool invocation, human oversight, evidence, cost, and operational controls. 

• Communicates complex architecture and AI concepts clearly to executives, business stakeholders, architects, engineers, vendors, and control partners. 

• Balances innovation with risk management, security, privacy, resilience, auditability, and compliance expectations in a regulated environment. 

• Provides architecture guidance that enables delivery teams to move forward safely, efficiently, and with clear decisions. 

• Frames architecture decisions in terms of business value, risk reduction, reuse, modernization, cost-effectiveness, and measurable outcomes. 

• Mentors’ architects and engineers, builds reusable architecture knowledge, and helps create a stronger internal bench for AI-enabled and broader solution delivery. 

Success Indicators 

• Delivery of high quality solution architectures that align with enterprise standards, business priorities, risk expectations, and delivery outcomes. 

• Improved architecture consistency and reuse across Corporate IT initiatives through effective use of reference architectures, approved patterns, reusable components, and architecture runway artifacts. 

• Successful enablement of AI-enabled, Generative AI, and Agentic AI solutions that are secure, reliable, governed, cost effective, and production ready. 

• Effective partnership with business, technology, risk, security, privacy, data, operations, and vendor stakeholders, with clear architectural decisions and accountable outcomes. 

• Visible contribution to the maturity of solution architecture practices, including stronger design reviews, clearer decision records, better delivery guardrails, and improved architectural health. 

• Growth of architecture and engineering capability through coaching, knowledge sharing, and practical guidance on both traditional solution architecture and AI-enabled solution patterns. 

What’s in it for you? 

• Great Place to Work® Certified for Most Trusted Executive Team in Canada – 2025, 2024 and 2023 

• Great Place to Work® Certified for Best Workplaces in Canada - 2025 

• Canada Order of Excellence for Mental Health at Work® certification from Excellence Canada. Sun Life is one of only four companies in Canada to ever receive this certification – 2024 

• Top Work Places® for Remote Work – Monster Canada - 2024 

• Great Place to Work® Certified for Best Workplaces in Canada – 2024 and 2022 

• Great Place to Work® Certified for Best Workplaces for Women in Canada - 2024 

• Flexible hybrid work model. #LI-Hybrid 

• Pension, stock and savings programs to help build and enhance your future financial security 

• Work and professional development that is united by our Purpose: to help Clients and Employees achieve lifetime financial security and live healthier lives 

• A friendly, collaborative and inclusive culture 

• Be part of our continuous improvement journey in developing the next greatest digital enterprise experience. 

• Competitive salary and bonus structure influenced by market range data 

• The opportunity to move along a variety of career paths with amazing networking potential