AI Technical Lead (Reliability Status, 5+ years) to design and integrate AI capabilities using
S.i. Systems • Regina
18 hours ago
Job type
- Contractor
Job description
Our banking client is seeking an AI Technical Lead (Reliability Status, 5+ years) to design and integrate AI capabilities using Microsoft Azure, Dynamics , 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 , 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 , 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 , 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