AI Adoption & Acceleration Manager

Devire Outsourcing IT is a B2B collaboration model for IT specialists delivering projects for leading clients. The client operates in the FMCG industry as one of the largest producers of tobacco and smoke-free products worldwide.

• Documented experience implementing AI, Machine Learning, and GenAI solutions in production environments within large organizations.
• Ability to translate business needs into technical requirements and influence solution choices.
• Experience collaborating with IT and data teams on integration, data pipelines, access management, security, and deployment lifecycle.
• Strong communication skills with management.
• Ability to work in ambiguous environments and structure complex business problems.
• Pragmatic, value-oriented approach focusing on business results.

Nice to have:

• Experience in Shared Services / GBS or large operational organizations.

• Knowledge of service management concepts like service catalogs and SLAs.

• Experience in MLOps or AI deployment governance.

• Experience building adoption and managing change in operational teams.

• Leadership in project execution, converting ambiguity into concrete results.

• Business understanding of operational processes and value drivers.

• Technological proficiency to assess and guide solution design without deep programming.

• Credibility with both business leaders and technical teams.

• Commitment to continuous development and tracking AI trends and best practices.

• Negotiation skills and ability to reconcile stakeholder priorities.

• Preferred continuous competence development such as recent AI, ML, or GenAI courses or certifications.

• Proven experience with projects, deployments, or case studies.

Creating AI use cases and translating business needs:

• Identify and qualify AI application opportunities with GBS service lines and process owners.
• Translate business problems into AI use cases with defined scope, business value hypothesis, constraints, and success criteria.
• Prepare business materials and summaries for management.

Implementing AI in enterprise environments:

• Lead end-to-end AI solution deployment including requirements gathering, design, development coordination, testing, UAT, deployment preparation, and hypercare support.
• Integrate AI solutions into daily team processes.
• Ensure compliance with security, regulatory, privacy, and reliability requirements in collaboration with IT and risk management teams.

Product implementation and scaling:

• Define repeatable patterns and playbooks for scaling AI solutions across markets and service lines.
• Support standardization by creating reusable components, deployment templates, and documentation standards.
• Support AI CoE operations in governance, prioritization, request management, and portfolio reporting.

Adoption, change management, and business value realization:

• Plan AI adoption including stakeholder mapping, training preparation, communication, and feedback collection.
• Define and monitor business benefits using clear KPIs and dashboards.
• Ensure AI deployments translate into real business outcomes, not just technology delivery.

Cross-functional collaboration and stakeholder management:

• Build strong relationships with service lines, process owners, Operational Excellence teams, IT teams (architecture, integration, platforms, security), and data teams (engineering, analytics, model lifecycle).
• Present progress and recommendations to senior stakeholders.
• Facilitate decisions on trade-offs, risks, and mitigation actions.