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About the Role
Seeking a knowledgeable and driven Analyst to design, implement, operationalize, and govern AI-enabled solutions using enterprise platforms like Microsoft Copilot Studio, Azure AI Foundry, Power Platform, Microsoft Fabric, and SAP BTP AI Core. The role focuses on delivering business value, productivity improvements, and automation at scale, while ensuring AI solutions are scalable, secure, compliant, and aligned with organizational governance principles.
Responsibilities
- Design, implement, and deliver end-to-end AI solutions using enterprise platforms such as Copilot Studio, Azure AI Foundry, Power Platform, Microsoft Fabric, and SAP BTP AI Core.
- Translate business requirements into scalable AI-enabled solutions and workflows.
- Configure, integrate, and deploy AI capabilities within Microsoft 365, Power Platform, Azure, SAP, and other enterprise applications.
- Ensure proper integration with approved data sources and enterprise architecture standards.
- Develop and maintain AI solution registries, risk registries, governance frameworks, policies, standards, and procedures.
- Conduct AI risk assessments.
- Ensure solutions comply with organizational policies, security requirements, privacy standards, and data residency regulations.
- Manage Azure AI Foundry, Copilot, and AI agent governance across the organization.
- Support business unit AI champions and enterprise AI initiatives.
- Work closely with business analysts, clients, IT teams, security teams, and vendors to identify opportunities, implement solutions, and drive successful adoption of AI capabilities.
- Perform reviews of AI solutions to ensure alignment with business requirements, architectural standards, governance requirements, and optimal execution patterns.
- Promote awareness and adoption of AI technologies through education, coaching, demonstrations, and knowledge-sharing initiatives.
- Provide guidance to stakeholders on AI capabilities, limitations, best practices, and appropriate usage.
- Establish, document, and maintain AI development standards and best practices.
- Evaluate emerging technologies and recommend enhancements to improve organizational productivity and automation.
Requirements
- Degree in Computer Science, Software Engineering, Information Technology, Data Analytics, Data Engineering, Data Science, or equivalent combination of education and experience.
- Minimum of 5 years of relevant technology experience in software development/engineering, cloud engineering, solution architecture, automation / intelligent automation or ML / AI engineering.
- Minimum of 2 years of significant hands-on experience with AI, building GenAI / LLM solutions.
- Experience delivering AI initiatives from concept through production deployment.
- Cloud certification(s) preferred, particularly Microsoft Azure certifications.
- Ability to communicate complex technical concepts to both technical and non-technical audiences.
- Experience working in cross-functional teams and leading stakeholder engagements.
- Ability to attain or currently hold Canadian Federal Government Enhanced Reliability Status clearance.
Skills
- Strong knowledge of enterprise AI platforms, including Microsoft Copilot Studio, Azure AI Foundry, Azure AI Services, Power Platform, Microsoft Fabric, and SAP BTP AI Core or equivalent platforms.
- In-depth understanding of AI solution architecture, design principles, modeling techniques, lifecycle management, and deployment strategies.
- Experience implementing AI governance frameworks, policies, standards, and controls to ensure security, compliance, consistency, and responsible AI usage.
- Strong understanding of APIs, integrations, workflow automation, and enterprise system integration patterns.
- Working knowledge of programming and scripting languages such as Python, JavaScript, Java, PowerShell, and SQL.
- Understanding of Azure DevOps and modern software delivery practices.
- Knowledge of prompt engineering, AI agent orchestration, and generative AI solution development.
- Understanding of data protection, privacy requirements, AI risk considerations, and enterprise governance frameworks.
Experience Level
- Minimum of 5 years of relevant technology experience
- Minimum of 2 years of significant hands-on experience with AI, building GenAI / LLM solutions
Education Level
- Degree in Computer Science, Software Engineering, Information Technology, Data Analytics, Data Engineering, Data Science, or equivalent combination of education and experience.