Sr. Solution Architect

Sr. Solution Architect

Our Technology team wakes up every day with one goal in mind - connecting Canadians to the people and things that matter most. Together, we are proud to support 30 million Canadians each month through managing a robust portfolio that champions leading-edge technology. We drive large-scale, complex, and high-visibility technology projects and programs that shape the future of technology in Canada and expand connectivity from coast to coast. If you are interested in being a part of this, consider applying for the following opportunity:

Who we're looking for:

We're looking for a hands-on Senior Solution Architect to lead the design and deliver scalable, secure, and reusable data and AI solutions.

This role sits within the Data & AI team and provides technical leadership across end-to-end data and AI architecture, from requirements and design through to implementation. You'll work closely with business partners, architects, engineers, security, governance and platform teams to translate complex business needs into practical, production-ready solutions across data, integration, and analytics environments.

What you'll do:

Lead Data Solution Design

• Lead the assessment of complex business and technical requirements and translate them into end-to-end data and AI solutions.
• Own solution architecture across data processing, storage, integration, consumption, security and AI enabled capabilities.
• Build High-Level Designs (HLDs) and contribute to Detailed Design Documents (DDD), ensuring consistency across the solution lifecycle.
• Evaluate solution alternatives and make architectural recommendations based on business requirements, technical constraints, cost, scalability, performance, and operational considerations.
• Identify architectural risks, dependencies, assumptions, and design trade-offs early in the solution lifecycle.

Define Data and AI Architecture Patterns

• Design conceptual, logical, and physical data architectures and models that promote performance, interoperability, and reuse.
• Define patterns for structured, semi-structured, and unstructured data, including batch, streaming, API, and event-driven integration and consumption.
• Develop reusable architecture patterns for GenAI, RAG, enterprise and vector search, document processing, semantic models, and AI agents.
• Design secure integration patterns across enterprise data platforms, AI/ML platforms, LLMs, APIs, applications, and analytics solutions.
• Incorporate identity, RBAC, least-privilege access, data classification, privacy, and governance requirements into solution designs.

Provide Technical Leadership Through Delivery

• Provide architectural leadership to project teams throughout the delivery lifecycle, from initial discovery through implementation and production readiness.
• Work closely with engineering teams to ensure designs are delivered as designed
• Participate in design reviews and provide technical direction when implementation decisions require architectural guidance.
• Support the transition of AI solutions from proof of concept to governed production implementations.

Collaborate Across Teams

• Act as a senior technical partner to business stakeholders, architects, engineers, data science, analytics, security, governance, and platform teams.
• Align solution designs with enterprise data and AI strategies, security standards, data quality requirements, and stewardship practices.
• Communicate architectural decisions, risks, trade-offs, and recommendations clearly to technical and business stakeholders.
• Partner with AI and Data Science teams to define data and architecture requirements for AI/ML and GenAI solutions.

Assess and Improve Solutions

• Assess existing data architectures to identify improvement opportunities for modernization, simplification, consolidation, and improvement.
• Perform impact assessments using data lineage, object dependencies, and usage information.
• Identify technical debt and recommend practical remediation or modernization strategies.
• Evaluate emerging data and AI technologies through technical assessments and proofs of concept.
• Identify architectural risks associated with AI solutions, including data exposure, inappropriate data access, model dependency, and solution reliability.
• Stay current with evolving data platforms, AI architecture patterns, model capabilities, and responsible AI practices.

What you bring:

• We recognize strong candidates come from different paths. You might be a great fit if you have:
• University degree in computer science, information technology, data management or equivalent.
• Strong experience architecting solutions across multiple systems, platfo