Principal AI Technology & Innovation Specialist at NTT Ltd.

Your day at NTT DATA

• The Principal AI Technology & Innovation Specialist is a highly skilled subject matter expert with deep expertise in emerging AI technologies, advanced analytics, and AI system architecture. This role is accountable for the strategic assessment, experimentation, and enablement of cutting-edge AI solutions within the organization, driving innovation and ensuring AI readiness across internal platforms and client-facing services.
• The primary objective of this role is to stay at the forefront of AI innovation by evaluating, piloting, and recommending next-generation AI technologies and vendor capabilities. The specialist serves as a strategic advisor and hands-on innovator, influencing architecture, engineering, and product teams to integrate AI capabilities in scalable and responsible ways. This includes defining technical blueprints, building AI proof-of-concepts, and supporting adoption through alignment with IT and enterprise architecture.

Key Responsibilities

• Lead the evaluation and strategic assessment of emerging AI technologies, platforms, and vendor solutions, advising on technical and ethical feasibility.
• Design and guide the development of AI capabilities and innovation pilots, translating business goals into AI-enabled solutions.
• Define architectural blueprints for integrating AI technologies into IT systems and product platforms, ensuring security, scalability, and alignment with enterprise standards.
• Develop frameworks for responsible AI adoption including model evaluation, explainability, privacy, compliance (e.g., EU AI Act), and ethical use.
• Partner with product and platform teams to align AI innovations with enterprise technology strategy and business outcomes.
• Drive initiatives for AI prototyping, proof-of-concepts (PoCs), and production readiness assessments.
• Monitor vendor roadmaps and contribute to the strategy for selecting and onboarding external AI capabilities.
• Act as a center of excellence for AI within the IT organization, driving awareness, knowledge sharing, and standardization.
• Collaborate with enterprise architects and platform leads to integrate AI tools into data infrastructure, software architecture, and cloud environments.
• Perform technical due diligence on third-party AI services and models, ensuring fit-for-purpose and cost-effective solutions.
• Continuously improve internal innovation processes and methodologies to increase the speed and quality of AI-driven transformation.

Knowledge and Attributes

• Deep knowledge of modern AI paradigms including generative AI (e.g., LLMs), machine learning infrastructure, AI model lifecycle, and MLOps.
• Strong understanding of AI model risks and evaluation techniques, with experience applying responsible AI principles in enterprise environments.
• Excellent ability to assess multi-vendor and open-source AI offerings for enterprise adoption.
• Advanced knowledge of reference AI architectures, integration models, and cloud-based AI toolchains.
• Ability to translate business needs into technical AI strategies, architectures, and implementation roadmaps.
• Excellent communication and stakeholder management skills across technical, executive, and vendor audiences.
• Strategic thinker with the ability to rapidly assess the value and risks of new AI technologies and innovation trends.

Academic Qualifications and Certifications

• Bachelor’s degree or equivalent in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Advanced degrees (MSc/PhD) in AI/ML fields preferred.
• TOGAF, COBIT, or related enterprise architecture certifications are beneficial.
• Certifications in machine learning or cloud-based AI platforms (e.g., AWS Certified Machine Learning Specialty, Google Cloud AI Engineer) are advantageous.

Required Experience

• Extensive experience in leading enterprise AI innovation and architecture initiatives.
• Proven track record of evaluating, piloting, and operationalizing AI solutions in enterprise environments.
• Experience working across multiple industries and large-scale IT organizations.
• Hands-on experience in AI/ML development, integration, and lifecycle management.
• Familiarity with regulations governing AI use, such as the EU AI Act, and experience in operationalizing compliance measures.

Method of Application
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