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AI Solution Architect

eqbank · Toronto

New
Senior 🇬🇧 English
Microsoft Azure Azure AI Foundry Azure OpenAI APIM AI gateways vector stores AI Search Google Cloud Platform Vertex AI Gemini Enterprise Agent Platform Agent Builder Agent Engine BigQuery LangGraph LangChain LangSmith Model Context Protocol Agent2Agent microservices RESTful Microsoft Fabric Synapse Power BI

Job description

About the role

The AI Solution Architect is a senior individual‑contributor within the Solutions Architecture team, responsible for designing and delivering AI‑enabled solution architectures for enterprise initiatives. The role focuses on translating business and technical requirements into concrete, secure, and scalable designs on Microsoft Azure and, when needed, Google Cloud Platform.

Key responsibilities

  • Design and document solution architecture artifacts (component, integration, and data‑flow diagrams) for initiatives such as PC Financial integration, eCIF, and AML/Risk/Finance/Treasury, ensuring alignment with enterprise standards.
  • Develop end‑to‑end AI/agentic solutions using Azure AI services, Vertex AI, LangGraph, LangChain, and related orchestration frameworks, including security, observability, and data‑access patterns.
  • Provide technical guidance and mentorship to developers and analysts, collaborate with Enterprise Architecture, AI Centre of Enablement, Cyber Security, and external partners, and support on‑call production responsibilities.

Required profile

  • Bachelor’s degree in Computer Science, Engineering or related field (post‑graduate degree is a plus).
  • 8+ years of IT experience with at least 5 years designing and delivering solution, application, or integration architecture for specific projects, operating as a senior individual contributor.
  • Hands‑on experience architecting AI and agentic solutions on Microsoft Azure and/or Google Cloud Platform, including landing‑zone patterns and compliance considerations.

Required skills

  • Microsoft Azure (Azure AI Foundry, Azure OpenAI, APIM AI gateways, vector stores, AI Search)
  • Google Cloud Platform (Vertex AI, Gemini Enterprise Agent Platform, Agent Builder, Agent Engine, BigQuery)
  • LangGraph, LangChain, LangSmith orchestration frameworks
  • Model Context Protocol (MCP) and Agent2Agent (A2A) interoperability standards
  • Microservices, RESTful, event‑driven, cloud‑native architecture patterns
  • Relational and NoSQL databases for transactional and analytical workloads
  • Data platform tools (Microsoft Fabric, Synapse, Power BI)

Questions fréquentes

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Source : ats:lever

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Published 1 day ago

Expires 1 month from now

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eqbank

Toronto