AI Project Manager W/M
- Design and deliver AI training programs for all functions (content, workshops, live sessions, materials).
- Create and maintain operational documentation: guides, playbooks, FAQ, prompt examples, "do & don't".
- Provide hands-on support to teams to select the right uses and embed them into workflows.
- Build an AI literacy culture and encourage teams to surface opportunities from the field.
- Identify AI opportunities to improve internal processes (Tech, Product, Sales, Support, Ops, Finance...).
- Serve as the main internal point of contact regarding AI governance for any internal business initiatives
- Evaluate, select, and deploy AI tools and/or components (cloud AI services, assistants, automations) aligned with business needs and compliance constraints.
- Participate to the development, configuration, or customization of internal tools: quality, security, scalability, UX.
- Work with technical teams and support functions to integrate tools into existing systems (SaaS, workflows, knowledge bases).
- Define and enforce an AI governance framework: usage rules, data classification, contractual requirements, access management, traceability.
- Implement security measures to prevent uncontrolled usage (data leakage risks, Shadow AI, unsafe practices).
- Track evolving AI risks (technical, legal, privacy) and continuously improve standards.
- Lead tool rationalization (AI, automation, knowledge): map the landscape, identify redundancies, propose decisions.
- Pilot AI costs with the FP&A business partner: track spend (licenses, usage-based, etc.), allocate costs when relevant, set targets and guardrails.
- Maintain active watch on AI trends, emerging risks, and best practices for enterprise adoption.
- Build a network of relevant contacts (experts, communities, partners) when useful.
- Structure and run knowledge-sharing rituals: retrospectives, demos, use-case catalog.
- Strong experience (typically 4+ years) delivering IT / business transformation, operational efficiency, rationalization, and/or knowledge management programs, ideally in complex environments.
- Solid understanding of AI tooling (LLMs, assistants, automation) and how to integrate it into workflows.
- Strong analytical and problem-solving skills: turn ambiguous requests into measurable execution plans.
- Excellent communication and training skills, able to explain technical concepts to non-technical audiences.
- Pragmatic approach: maximize value while controlling risk.
- Autonomous and outcome-driven: deliver and drive adoption, not just framing.
- Ability to influence and align business and technical stakeholders.
- Strong sense of responsibility for data protection, privacy, and security (classification, access, contracting, risk).
- Comfortable in a fast-paced, multi-stakeholder, high-growth environment.
- Fluent in English and French (written and spoken).
- Strong plus: experience deploying AI solutions in an enterprise context (use cases, tooling, change, impact measurement).
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