Position Objective 

Own the adoption and enablement agenda for Google Cloud, Vertex AI, Gemini, and related AI services within customer and enterprise environments. Ensure that AI initiatives move beyond demonstrations by building stakeholder commitment, user capability, responsible-use practices, measurable adoption, and repeatable operating models. The role complements solution architects and engineering leads by ensuring that people, processes, and business use cases are ready to realize the value of the technical solution. 

Key Responsibilities 

AI Adoption Strategy and Business Alignment 

• Develop and execute adoption strategies for Google Cloud, Vertex AI, Gemini, and enterprise AI solutions in line with customer objectives and the Google Engineer business roadmap. 

• Assess organizational readiness, user needs, business priorities, adoption barriers, and change impacts across functions and stakeholder groups. 

• Define adoption roadmaps, stakeholder plans, communication plans, enablement journeys, and measurable success criteria for each engagement. 

• Partner with business and technology leaders to secure sponsorship, align priorities, and embed AI initiatives into day-to-day operating models. 

Google Cloud, Vertex AI, and Gemini Enablement 

• Design and deliver practical enablement programs covering Google Cloud concepts, Vertex AI capabilities, Gemini use cases, responsible AI, security, and effective human–AI collaboration. 

• Create role-based learning paths, workshops, demonstrations, playbooks, quick-reference guides, communications, and communities of practice for technical and non-technical audiences. 

• Translate complex cloud, data, AI, and Generative AI concepts into clear business language and hands-on learning experiences. 

• Coordinate with solution architects and engineering teams so that enablement materials accurately reflect the implemented solution, controls, and operating procedures. 

• Promote responsible AI behaviors, including appropriate use, human oversight, data protection, security, model limitations, and escalation routes. 

AI Use-Case Discovery and Production Adoption 

• Work with business functions and customer teams to identify, prioritize, and validate high-value AI and automation use cases. 

• Facilitate discovery workshops, design-thinking sessions, stakeholder interviews, and value-assessment activities for Google AI opportunities. 

• Support pilots and proof-of-value activities by defining user journeys, adoption hypotheses, feedback loops, and readiness criteria. 

• Help transition successful use cases from pilot to production by coordinating user readiness, process changes, documentation, support models, and adoption communications. 

• Capture and share reusable patterns, lessons learned, success stories, and customer references across the Google Engineer business. 

Stakeholder Engagement and Change Leadership 

• Act as a trusted advisor to customer executives, business leaders, product owners, HR or learning teams, and technology stakeholders on AI adoption and change priorities. 

• Lead change-impact assessments, stakeholder mapping, communication activities, feedback collection, and resistance-management actions. 

• Facilitate executive briefings, steering meetings, enablement sessions, user forums, and cross-functional working groups. 

• Coordinate distributed NTT DATA, customer, partner, and Google-aligned teams to maintain consistent messages, expectations, and adoption actions. 

• Build trusted relationships in international and cross-cultural environments, including engagements with APAC stakeholders when required. 

Adoption Governance, Measurement, and Continuous Improvement 

• Define and maintain adoption KPIs covering reach, participation, readiness, active usage, use-case progression, user confidence, satisfaction, and realized business value. 

• Maintain adoption dashboards, executive reports, risk and issue logs, decision records, and action trackers with clear owners and due dates. 

• Monitor user feedback, usage trends, business outcomes, and emerging risks; recommend corrective actions and continuous-improvement initiatives. 

• Ensure adoption activities align with customer governance, security, privacy, compliance, responsible AI, and operational-readiness requirements. 

• Contribute to proposals, statements of work, delivery plans, and service-improvement initiatives by articulating the people and adoption work required for sustainable outcomes. 

Essential Qualifications 

The role requires a senior adoption and transformation professional who can connect Google Cloud and AI engineering capabilities with user behavior, business change, and measurable customer outcomes: 

• Bachelor’s degree or higher in Information Technology, Computer Science, Artificial Intelligence, Data Science, Engineering, Business, Organizational Development, Change Management, Education, or a related discipline. 

• At least 8 years of experience in digital transformation, technology adoption, organizational change, business transformation, consulting, learning enablement, or a comparable field. 

• At least 3 years of experience leading enterprise AI, Generative AI, automation, cloud, data, or emerging-technology adoption initiatives from strategy through measurable implementation. 

• Proven experience turning complex Google Cloud and AI capabilities into practical user journeys, learning programs, operating changes, and sustained adoption outcomes. 

• Practical knowledge of Google Cloud and AI concepts, including Vertex AI, Gemini, data and analytics services, Generative AI use cases, model limitations, responsible AI, security, and production readiness. 

• Demonstrated ability to design and facilitate executive briefings, workshops, role-based training, communities of practice, and cross-functional enablement programs. 

• Experience defining adoption metrics, analyzing user feedback and usage data, building dashboards or reports, and linking adoption activity to business value. 

• Strong program management, stakeholder management, facilitation, communication, presentation, analytical, influencing, and problem-solving skills. 

• Professional English communication skills and the ability to work effectively with international customers, engineering teams, and senior stakeholders. 

Preferred Qualifications 

• Google Cloud certification, such as Cloud Digital Leader, Associate Cloud Engineer, Professional Cloud Architect, or Professional Machine Learning Engineer, or equivalent practical experience. 

• Hands-on exposure to Vertex AI, Gemini, BigQuery, Cloud Storage, Google Workspace AI capabilities, prompt design, RAG concepts, AI evaluation, or enterprise AI governance. 

• Prosci, ADKAR, ACMP, CCMP, Lean Change, Agile, Scrum, PMP, or comparable change and delivery certification. 

• Experience with enterprise learning, collaboration, adoption analytics, or service-management platforms such as Google Workspace, Jira, Confluence, ServiceNow, or comparable tools. 

• Experience in consulting, technology services, managed services, cloud migration, AI transformation, or enterprise platform modernization. 

• Experience supporting APAC clients or multinational organizations; English language proficiency is highly desirable.