**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.