Genai Solution Architect
Role purpose : As a Solution Architect GenAI Solutions, you will lead the design, development, and implementation of Generative AI (GenAI) solutions within Vodafone Italy's technology ecosystem.
You will collaborate with cross-functional teams to architect AI-driven solutions that enhance business processes, improve customer experiences, and drive operational efficiencies.
This role is critical for harnessing the potential of emerging AI technologies, ensuring they align with Vodafone's strategic goals.
Key accountabilities and decision ownership : Solution Design & Architecture : Design and architect scalable, secure, and high-performance GenAI solutions to meet business needs across various departments (, customer service, marketing, sales, and operations). Innovation & Strategy : Develop AI strategies that align with Vodafone Italy's long-term goals, focusing on cutting-edge generative AI technologies (, 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 GenAI solutions adhere to the highest security, privacy, and regulatory standards (, 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 Proven Experience in AI / ML : At least 5 years of experience in AI / ML, with a strong focus on architecting generative AI solutions. Technical Expertise : Deep understanding of generative models, NLP, transformers, and large language models (, GPT, BERT). Proficiency with AI development frameworks like TensorFlow, PyTorch, 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 DevOps methodologies to lead projects in a fast-paced, dynamic environment. AI Certifications : Certifications in AI, cloud computing, or solution architecture from recognized organizations (, AWS Certified Machine Learning, Microsoft Certified : Azure AI Engineer).
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