Senior Enterprise AI Solutions Lead

Senior Enterprise AI Solutions Lead

Location: Regina, SK

Work Model: 100% Onsite – Monday to Friday, 5 days a week in office (Downtown Regina, SK)

Role Description

You will lead and deliver AI initiatives independently in collaboration with the business, from discovery through solution design, hands-on implementation, production support, and benefits realization.

You will work with business stakeholders to assess opportunities, define scope and priorities, and see approved initiatives through to measurable outcomes.

Our AI delivery environment includes Azure Foundry and related Azure services, ChatGPT Enterprise, Microsoft Copilot, Databricks, .NET, and Python. Solutions may use existing enterprise tooling, AI services, APIs and SDKs, vector indexes, and standard or custom Model Context Protocol (MCP) servers and tools.

This role is predominantly hands-on project delivery and includes technical leadership, stakeholder coordination, and production implementation.

The preferred platform and language qualifications below are rated assets; candidates are not required to possess every preferred qualification.

Key Responsibilities

• Lead discovery and scoping, define requirements and acceptance criteria, estimate delivery effort, and establish expected benefits and measures of success.
  
• Design solution architectures in collaboration with Enterprise Architecture and select appropriate AI services, software development kits, data access methods, and integration approaches within the approved environment.
  
• Implement AI solutions through production code and approved platforms, including AI agents, chatbots, retrieval over enterprise information, and workflows that use enterprise APIs and MCP tools.
  
• Plan and complete testing, quality evaluations, and production deployment, working with the appropriate teams on security, permissions, data access, and operational readiness.
  
• Support production solutions, monitor quality, reliability, and usage costs, and address defects, changes, and enhancements.
  
• Work with business owners to validate delivered outcomes, measure realized benefits against agreed baselines, and identify opportunities for improvement.
  
• Maintain technical and operational documentation, transfer knowledge, and complete support handover.
  

Must-Have Skills

1. Minimum of 5 years of experience delivering software solutions.
   
2. Minimum of 2 years of experience developing AI solutions.
   

Technical Skills and Qualifications

• Recognized bachelor's degree or technical diploma in Computer Science, Information Systems, Engineering, or a related discipline.
  

Minimum 3 Years of Experience

• Development using C# .NET.
  
• Development using Python.
  

Minimum 2 Years of Experience

• Developing and deploying AI solutions using Azure Foundry or a comparable AI development platform.
  
• Developing AI agents and chatbots, including tool calling, workflow orchestration, and integration with enterprise APIs.
  
• Implementing Retrieval-Augmented Generation (RAG), embeddings, vector indexes, and grounded responses over enterprise information.
  
• Integrating AI services through APIs and SDKs, including authentication, permissions, error handling, and testing.
  
• Defining and applying AI quality evaluations and acceptance criteria, including handling incorrect responses and failed tool actions.
  
• Using Git, code reviews, automated testing, and CI/CD processes.
  
• Using AI-assisted and agentic software development tools, such as GitHub Copilot, Codex, or equivalent.
  

Minimum 1 Year of Experience

• Developing solutions and workflows using ChatGPT Enterprise.
  
• Using or integrating with Databricks.
  
• Developing custom Model Context Protocol (MCP) servers or integrating AI solutions with MCP tools, including enterprise data services such as Databricks.
  

Role-Specific Experience – Minimum 2 Years

• Leading AI initiatives independently through discovery, scoping, prioritization, architecture, implementation, support, and benefits realization.
  
• Deploying and supporting production AI solutions, including monitoring, usage cost management, and operational handover.
  
• Working with business stakeholders to assess value, establish benefit measures, and evaluate realized outcomes.