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About the Role

We help customers turn technology investment into meaningful progress for their businesses and the people they serve. Our culture values curiosity, inclusion, accountability and trusted collaboration. We seek architects who combine sound judgment with hands-on engineering, share what they learn and create an environment where colleagues and customers can challenge ideas openly. A frontier company is not defined by adopting the newest technology first. It is defined by the judgment to translate emerging capabilities into secure, reliable and measurable outcomes. This means framing ambiguous problems, making explicit tradeoffs among cost, reliability and speed, and deciding responsibly with incomplete information. It also means knowing when not to use AI, controlling scope and establishing what must be true before a solution is ready for release. ISD’s frontier consulting practice brings industry understanding, solution expertise and engineering discipline together. We use AI to strengthen how we explore, design and deliver, while keeping people accountable for decisions and quality. We build early working artifacts, validate them with customers and learn from delivered work rather than self-assessment. Adoption, change and capability transfer begin at the outset, so progress becomes sustained customer value rather than a successful demonstration alone. Based in the Greater Toronto Area, the Senior Solution Architect in ISD Canada will lead strategic customer engagements, with a particular focus on financial services. The role requires fluency in customer workflows, data and risk considerations before selecting products or platforms. You will partner with executives and customer engineering teams to establish a credible baseline, define success measures and connect architecture decisions to business priorities across the Toronto and Canadian market. This is both a strategic and a hands-on architecture role. You will guide multidisciplinary teams, maintain full-stack depth and collaborate with specialists to validate critical design choices in working solutions. A practical AI Usage Plan will help each significant engagement improve delivery with measured benefits, clear accountability and appropriate guardrails. The opportunity is to deliver reviewed, tested and operationally ready solutions, help customers adopt them, and create reusable patterns and capabilities that other teams actually use.

Responsibilities

Engage executives to understand business priorities, establish baseline performance and define measurable outcomes and success criteria that guide architecture and investment decisions.
Translate business requirements into actionable solution architecture, applying financial-services workflow, data and risk fluency to the customer’s operating context before recommending products or platforms.
Challenge assumptions, frame ambiguous problems and make explicit cost, reliability and speed tradeoffs. Decide with incomplete data, control scope and say no when a proposed approach, including AI, is not justified.
Develop clear, decision-oriented proposals for executive audiences that explain options, dependencies, risks and the recommended path in terms of business outcomes.
Serve as Lead Architect and accountable technical authority on complex engagements, aligning design decisions and hands-on technical direction with customer outcomes.
Lead and mentor multidisciplinary teams through trust, candor and shared ownership. Encourage constructive challenge, make responsibilities clear and support colleagues in developing sound technical judgment.
Govern human and AI-assisted teams, including agent orchestration, context, retrieval and memory. Define action authority, authorization boundaries, blast radius, human approvals and auditability so AI operates within explicit controls.
Partner with Program Directors and Project Managers to maintain technical governance, delivery quality and transparent management of scope, dependencies and risks.
Strengthen the architecture community through reusable patterns, mentoring and capability transfer. Share evidence from delivered work and help customer and delivery teams apply assets in practice.
Establish and execute an AI Usage Plan for each significant engagement as a practical operating plan, not a paperwork exercise. Define measurable benefits, accountable owners, appropriate use cases, verification responsibilities and guardrails.
Use AI across requirements, code, tests, documentation and architecture, with human review and verification appropriate to the work. Demonstrate improved throughput without sacrificing reviewed and tested quality.
Deliver the smallest viable working slice early, use demos and customer validation to test assumptions, and iterate on evidence. Seek credible proof-of-value in weeks where appropriate without compromising regulated-production readiness.
Measure cycle time, quality, cost and business value against the engagement baseline. Adapt the AI Usage Plan and delivery approach based on observed results rather than activity counts or self-assessment.
Maintain engineering discipline through architecture documentation, design reviews, code review, testing, CI/CD and operational readiness. Ensure that critical design choices are validated in working artifacts.
Conduct solution reviews that address security, reliability and maintainability, including AI evaluations, authorization controls and the behavior of agent-based components where relevant.
Identify risks proactively and establish evidence-based release criteria. Lead production go/no-go recommendations with explicit attention to unresolved risks, readiness gaps and customer operating requirements.
Promote shared engineering accountability and honest risk escalation. Surface limitations and uncertainty early, and work with delivery leaders and customer teams to resolve issues rather than defer them.
Create and maintain reusable, tested reference architectures, accelerators and frameworks. Validate that other teams can adopt them and use feedback from real engagements to improve them.
Apply broad Microsoft solution capability across Data & Analytics, AI & ML, Application Development and Cloud Infrastructure to shape end-to-end customer solutions.
Integrate data, applications, infrastructure, identity and security into cohesive architectures, with clear interfaces, dependencies and operational ownership.
Maintain technical depth in two to three domains while providing full-stack architectural guidance. Validate critical assumptions hands-on through code, prototypes, tests and working demonstrations.
Collaborate with specialists, product teams and customer engineers to resolve complex technical issues, apply the right expertise and transfer capability without losing end-to-end architectural accountability.
Shape strategic Toronto/Canada FSI opportunities and add-on scope tied to outcomes.
Drive & Accelerate production cloud solutions responsibly aligned with customer and Microsoft strategy.
Deliver Business and Operational Excellence, including adoption, realized value and customer capability transfer.

Requirements

Master's Degree in Computer Science, Information Technology, Engineering, or related field AND 10+ years experience in technology solutions, practice development, architecture, consulting, and/or technology domain (e.g., Security) OR Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field AND 12+ years experience in technology solutions, practice development, architecture, consulting, and/or technology domain (e.g., Security) OR equivalent experience.
4+ years managing multiple, complex projects or portfolios.
2+ years experience leading blended, multidisciplinary teams.
Technical Skills — Full Stack Coverage Across: Data & AI, Azure Data Platform (Azure Synapse, Fabric, Data Factory, Databricks), AI & Machine Learning (Azure OpenAI, Azure AI Studio, Cognitive Services, MLOps), Big Data architectures (Lambda, Kappa), Enterprise Data Warehouse, Advanced Analytics, Application Development, Modern application architecture, microservices, API-first design, DevOps, CI/CD pipelines, GitHub Advanced Security, container platforms, App modernization, .NET, Java, and open-source software stacks, Cloud Infrastructure, Azure IaaS and PaaS services, subscription design, network architecture, Identity and Access Management (Azure AD, Entra), security architecture, Private/Hybrid/Public cloud configurations, migrations, and governance, Security, Security reviews, threat modeling, Zero Trust architecture, Credential theft mitigation, compliance, and regulatory considerations in Canada.
Leadership & Delivery Capabilities: Demonstrated ability to lead solution delivery as the Lead Architect on complex, multi-team engagements.
AI literacy — actively using AI tooling in day-to-day architecture and delivery work.
Experience writing and executing AI usage plans or equivalent AI integration strategies for customer engagements.
Ability to execute recognized Software Architecture methods, processes, and tools.
Experience applying engineering-grade practices: architecture review boards, design patterns, quality gates, test automation.
Ability to give compelling presentations to executive audiences, linking technical decisions to business outcomes.
Proven ability to build and sustain trusted relationships at the executive level (C-suite, VP, and Board) — engaging as a peer, not just a vendor, and maintaining those relationships across the full engagement lifecycle.

Skills

Data & AI
Azure Data Platform (Azure Synapse, Fabric, Data Factory, Databricks)
AI & Machine Learning (Azure OpenAI, Azure AI Studio, Cognitive Services, MLOps)
Big Data architectures (Lambda, Kappa)
Enterprise Data Warehouse
Advanced Analytics
Application Development
Modern application architecture
Microservices
API-first design
DevOps
CI/CD pipelines
GitHub Advanced Security
Container platforms
App modernization
.NET
Java
Open-source software stacks
Cloud Infrastructure
Azure IaaS and PaaS services
Subscription design
Network architecture
Identity and Access Management (Azure AD, Entra)
Security architecture
Private/Hybrid/Public cloud configurations
Migrations
Governance
Security reviews
Threat modeling
Zero Trust architecture
Credential theft mitigation
Compliance
Regulatory considerations in Canada
AI literacy
Software Architecture methods, processes, and tools
Engineering-grade practices
Architecture review boards
Design patterns
Quality gates
Test automation
Executive presentations

Location

Greater Toronto Area

Work Type

Full-time

Experience Level

Senior
10+ years
12+ years
4+ years
2+ years

Education Level

Master's Degree in Computer Science, Information Technology, Engineering, or related field
Bachelor's Degree in Computer Science, Information Technology, Engineering, or related field

Salary/Compensations

CAD $172,200 - CAD $334,000 per year

About the Company

We help customers turn technology investment into meaningful progress for their businesses and the people they serve.
Our culture values curiosity, inclusion, accountability and trusted collaboration.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Equal Opportunity

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.