Role purpose:

Key accountabilities and decision ownership:

• Innovation & Strategy: Develop AI strategies that align with Vodafone Italy’s long-term goals, focusing on cutting-edge generative AI technologies (e.g., GPT models, deep learning, and NLP).
• Collaboration & Stakeholder Management: Work closely with business leaders, data scientists, AI engineers, and external partners to gather requirements, present solutions, and ensure successful solution delivery.
• Technology Stack & Integration: Architect solutions that integrate with Vodafone’s existing tech stack, including cloud platforms (AWS, Google Cloud, Azure), APIs, and data analytics tools.
• Model Optimization & Deployment: Collaborate with AI and ML teams to ensure the proper training, fine-tuning, and deployment of generative models that are optimized for scale and performance.
• Security & Compliance: Ensure that all Gen AI solutions adhere to the highest security, privacy, and regulatory standards (e.g., GDPR) and Vodafone’s internal policies.
• Continuous Improvement: Stay updated on the latest trends in AI and machine learning technologies and apply them to enhance existing solutions.
• Mentorship & Leadership: Provide technical leadership to junior architects and engineers, fostering a culture of innovation and excellence within the AI team.

Required competencies, knowledge, and experience

• Technical Expertise: Deep understanding of generative models, NLP, transformers, and large language models (e.g., GPT, BERT). Proficiency with AI development frameworks like Tensor Flow, Py Torch, etc.
• Cloud Expertise: Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud), with a focus on AI/ML services and infrastructure.
• Solution Architecture: Experience in designing large-scale, distributed AI systems with an understanding of microservices architecture, APIs, and modern data platforms.
• Programming Languages: Strong skills in Python, Java, or other relevant languages used in AI development.
• Data Integration: Expertise in working with structured and unstructured data, data pipelines, and real-time data processing frameworks.
• Security & Compliance: Familiarity with GDPR, AI ethics, and data privacy practices, especially as they pertain to AI technologies.

Nice to have technical and professional qualifications:

• Telecommunications Industry Knowledge: Prior experience in the telecom industry or with AI-driven customer engagement platforms is highly desirable.
• Agile Methodology: Familiarity with Agile and Dev Ops methodologies to lead projects in a fast-paced, dynamic environment.
• AI Certifications: Certifications in AI, cloud computing, or solution architecture from recognized organizations (e.g., AWS Certified Machine Learning, Microsoft Certified: Azure AI Engineer).

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