AI Deployment & Enablement Manager

''•Toronto, ON

14h•CA$111,700 - CA$149,000•Hybrid

About The Position

The AI Deployment Manager owns the enterprise rollout, enablement, governance, and measurement of AI self-service tools across McCain’s global workforce. This hands-on delivery and program role turns AI licenses and platform access into meaningful, measurable adoption by helping teams understand which tools to use, how to use them responsibly, and how those tools deliver business value. You will oversee the deployment and adoption of tools including Anthropic Claude, Microsoft Copilot, other large language model solutions, and McCain’s centralized AI platform, AI Hub. You will also develop the reporting and governance capabilities needed to understand tool usage, adoption, cost, risk, and business outcomes across the organization.

Requirements

Seven or more years of experience in technology deployment, enablement, adoption, solutions delivery, or technical program management.
Demonstrated experience leading technology or platform rollouts at scale within a large or complex organization.
A proven record of increasing adoption and converting technology investments into sustained, meaningful usage.
Hands-on fluency with at least two enterprise AI tools, such as Anthropic Claude, Microsoft Copilot, or Google Gemini.
Strong reporting and analytical capabilities, including experience defining adoption and cost metrics, developing dashboards, and translating data into actionable recommendations.
Working knowledge of enterprise deployment technologies and practices, including SSO, SCIM, MDM-managed settings, and organizational change management.
Practical understanding of large language models and small language models, including tradeoffs involving cost, latency, accuracy, and data control.
Experience partnering with Information Technology, Security, Legal, and Privacy teams on governance, acceptable use, and responsible deployment.
Clear and effective written and verbal communication skills, with the ability to engage both executive leaders and front-line employees.

Nice To Haves

Experience deploying Claude Code or configuring multiple model backends through Amazon Bedrock, Google Vertex AI, Microsoft Foundry, or an LLM gateway such as LiteLLM or Bifrost is an asset.
Experience building AI capabilities within Microsoft Azure is an asset.
Familiarity with MCP server governance, cost and token attribution, business-unit chargeback models, or regulated global enterprise environments is an asset.

Responsibilities

Plan and lead the deployment of Claude and approved Claude enterprise capabilities, including Claude Enterprise, Claude Code, and Claude Cowork, from initial pilots through enterprise-scale rollout.
Build and own reporting for AI usage, adoption depth, workflow integration, cost, token consumption, risk indicators, and business outcomes.
Maintain a clear enterprise view of which AI tools are being used, by whom, for which purposes, and at what cost.
Develop practical guidance for selecting and using AI tools, in partnership with AI governance, Information Technology, Security, Legal, and Privacy teams.
Configure and support enterprise controls, including SAML 2.0 or OIDC single sign-on, SCIM provisioning, MDM-managed settings, MCP server allowlisting, session controls, data-retention policies, and audit logging.
Deploy Claude Code and support model-routing configurations using approved LLM gateways or platforms such as Amazon Bedrock, Google Vertex AI, or Microsoft Foundry.
Establish AI capabilities in Microsoft Azure where appropriate, using solutions such as Azure OpenAI, Azure AI services, Microsoft Foundry, and Azure infrastructure.
Provide executive sponsors with regular reporting and recommendations related to adoption, cost, risk, training, champion activation, workflow redesign, policy changes, and license allocation.
Identify and remove barriers to AI adoption while sharing field insights with internal stakeholders and technology vendors.
Lead and activate a cross-functional network of AI champions to encourage responsible adoption and help scale successful use cases.