Ai Solution Architect

About WorkanaWorkana
is the largest remote work platform for talent in Latin America. Our division focuses on matching exceptional professionals with leading and innovative companies around the globe.
About the ClientOur client is a leading Canadian financial institution seeking a senior AI Solution Architect to join its Solutions Architecture team. The organization is expanding its digital capabilities, integrating strategic business systems, and executing advanced machine learning, risk, and financial delivery programs.
This is a hybrid opportunity for professionals based in Toronto, Ontario.
Role OverviewAs an
AI Solution Architect, you will serve as a senior individual contributor responsible for designing, documenting, and delivering solution-level architecture for initiatives requiring AI, agentic workflows, and machine learning. You will translate business and technical requirements into implementable solution designs—including application architecture, integration patterns, data flows, and cloud technology selection for key initiatives across integration, customer data, risk, and finance programs.
You will design secure, scalable cloud-native AI solutions primarily on Microsoft Azure (with working exposure to GCP), leveraging frameworks like LangGraph and LangChain. You will partner with Enterprise Architecture, Security, and Governance teams to ensure designs align with enterprise security, RBAC, and risk standards while focusing on solving specific program challenges.
Selection ProcessThe process usually consists of 3 stages and takes on average 4 weeks to be completed, depending on eventual additional technical rounds or take-home tests.
Initial interview with Workana's recruiting team;
Cultural fit interview with the client;
Final interview with C-level.
As Workana has multiple clients, if you pass the first round with Workana's recruiting team, you may also be considered for other relevant opportunities if the initial opportunity does not move forward.
Responsibilities
Design and document comprehensive solution architecture artifacts, including component, integration, sequence, and data-flow diagrams.
Architect end-to-end AI and agentic solutions using modern ecosystems (e.G.,
LangGraph ,
LangChain ,
LangSmith ,
Azure AI Foundry ,
Vertex AI ).
Translate business requirements into concrete solution designs through collaborative working sessions with business analysts, developers, and product owners.
Select appropriate technology components and integration patterns (API, event-driven, batch) while balancing performance, cost, and maintainability.
Present architecture designs and intake requests to governance forums and review boards for technical approval.
Establish agentic workflow patterns, network isolation, private endpoints, managed identities, token governance, and observability for AI workloads.
Design data access and integration patterns across cloud data platforms ( Azure Fabric/Synapse ,
GCP BigQuery ) in alignment with data architecture standards.
Guide and mentor developers and technical teams on architecture standards, design decisions, and implementation details.
8+ years of progressive IT experience, including at least 5 years designing solution, application, or integration architecture for specific business initiatives.
Bachelor's degree in Computer Science, Computer Engineering, or a related field.
Hands-on experience architecting cloud-native AI and agentic solutions on
Microsoft Azure
( Azure AI Foundry ,
Azure OpenAI ,
APIM AI Gateways ) or
GCP
( Vertex AI ).
Demonstrated experience with agent orchestration frameworks ( LangGraph ,
LangChain ,
LangSmith ) and knowledge of agent interoperability protocols ( MCP ,
A2A ).
Strong background in microservices, RESTful APIs, event-driven architectures, and relational/NoSQL databases.
Working knowledge of Responsible AI, model governance, and cloud security controls (managed identities, private endpoints, RBAC).
Familiarity with enterprise data platforms and analytics tools ( Microsoft Fabric ,
Synapse, or
BigQuery ).
Fluent English is mandatory, as the role involves regular collaboration with an international team.
Bonus Points
Experience in the banking or financial services industry, including familiarity with regulatory compliance frameworks.
Active certifications such as Microsoft Certified: Azure Solutions Architect Expert, Azure AI Engineer Associate, or Google Cloud Professional Machine Learning Engineer.
Practical exposure to emerging AI gateways, vector stores, and model-evaluation tooling in enterprise production environments.
Availability to work in-office 2-3 times per week.
Compensation in CAD.
Career growth with international clients and dynamic projects.
This is a long-term independent contractor agreement with no additional benefits.
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