AI Technical Lead (Reliability Status, 5+ years)

Our banking client is seeking an AI Technical Lead (Reliability Status, 5+ years) to design and integrate AI capabilities using Microsoft Azure, Dynamics 365, and Power Platform

Drive AI adoption across enterprise application development in a high-impact banking environment. Scope includes designing and building AI-enabled solutions and integrations with Microsoft Azure, Dynamics 365, Power Platform, and API-based architectures; prototyping generative AI, AI agents, and AI-assisted development tools; and evaluating solutions for architecture, security, privacy, reliability, and maintainability while collaborating with developers, testers, architects, and product owners.

Contract, Remote, Working Hours: EST

Must Haves

• Based in Canada and legally authorized to work in Canada
• Eligible for Government of Canada Reliability Status clearance

Nice to Have

• 5+ years in software development, solution architecture, or technical leadership within enterprise application development
• 2+ years designing, developing, prototyping, evaluating, or integrating AI or generative AI capabilities
• 3+ years with Microsoft Azure, Dynamics 365, or Power Platform
• Developing and integrating solutions using REST APIs, SDKs, and cloud services
• Applying AI-assisted development tools such as GitHub Copilot or equivalent

Responsibilities

• Provide subject matter expertise to support AI adoption across software development, testing, deployment, and application support
• Design and develop AI-enabled solutions and integrations that complement Microsoft Dynamics 365, Power Platform, Azure, and API-based architectures
• Prototype and evaluate emerging AI technologies and translate promising developments into practical use cases for the Scrum team
• Explore the use of generative AI, AI agents, and AI-assisted development tools within software engineering workflows
• Identify opportunities to apply AI to software testing and quality engineering, including test design, test automation, and defect analysis
• Explore opportunities to improve DevOps and software deployment processes through AI-assisted automation
• Establish reusable technical approaches, patterns, and components to enable consistent adoption across applications