AI Solution Architect

Workana

. Design and document comprehensive solution architecture artifacts, including component, integration, sequence, and data-flow diagrams .

Posted 10/5/2026contractToronto • CanadaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and documenting comprehensive solution architecture, particularly for AI and agentic solutions on cloud platforms like Microsoft Azure and GCP. Proficient in translating business requirements into technical designs while ensuring alignment with enterprise security and governance standards.

Highest-signal resume keywords

Solution Architecture DesignCloud-Native AI SolutionsLangGraph, LangChain, LangSmithAzure AI Foundry, Vertex AIMicroservices and RESTful APIs

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Solution ArchitectureIntegration ArchitectureAI WorkloadsData Integration PatternsEvent-Driven ArchitectureRelational DatabasesNoSQL DatabasesAgent Orchestration FrameworksAPI DesignData Architecture Standards

Soft Skills

CollaborationMentoringCommunicationPresentation SkillsProblem-Solving

Tools & Technologies

Microsoft AzureGCPAzure FabricAzure SynapseBigQueryAPI ManagementEvent-Driven SystemsManaged IdentitiesToken GovernanceObservability Tools

Certifications & Qualifications

Microsoft Certified: Azure Solutions Architect ExpertAzure AI Engineer AssociateGoogle Cloud Professional Machine Learning Engineer

Industry Keywords

BankingFinancial ServicesRegulatory ComplianceResponsible AICloud Security Controls

Tech Stack

Tools & technologies

AzureBigQueryCloudGoogle Cloud PlatformMicroservicesNoSQL

About the role

Key responsibilities & impact

Design and document comprehensive solution architecture artifacts, including component, integration, sequence, and data-flow diagrams
Architect end-to-end AI and agentic solutions using LangGraph, LangChain, LangSmith, Azure AI Foundry, and Vertex AI
Translate business requirements into concrete solution designs through collaborative working sessions with business analysts, developers, and product owners
Select technology components and integration patterns, including API, event-driven, and 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 Azure Fabric/Synapse and GCP BigQuery in alignment with data architecture standards
Guide and mentor developers and technical teams on architecture standards, design decisions, and implementation details
Partner with Enterprise Architecture, Security, and Governance teams to align designs with enterprise security, RBAC, and risk standards

Requirements

What you’ll need

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
Experience in banking or financial services, including familiarity with regulatory compliance frameworks (bonus)
Active certifications such as Microsoft Certified: Azure Solutions Architect Expert, Azure AI Engineer Associate, or Google Cloud Professional Machine Learning Engineer (bonus)
Practical exposure to emerging AI gateways, vector stores, and model-evaluation tooling in enterprise production environments (bonus)
Availability to work in-office 2–3 times per week (bonus)

Benefits

Comp & perks

Compensation in USD
Career growth with international clients and dynamic projects
Long-term independent contractor agreement
No additional benefits