Data & AI Architect

Company Description Xebia is a global, award-winning, AI-first consulting, software engineering, and training company that helps organizations turn AI strategies into production-ready solutions. Operating as a single global team, Xebia combines deep human expertise with AI to deliver high-impact digital and AI transformation. The company uses a flexible hybrid delivery model with client-facing teams in the US and Europe, nearshore capacity in Poland and Latin America, and a major offshore hub in India. This structure offers faster time-to-value, access to specialized AI and digital talent, and scalable solutions tailored to business needs. With round-the-clock delivery and a focus on attracting and retaining top global talent, Xebia enables organizations to build, scale, and innovate with confidence.Role Description The Data & AI Architect is a full-time role based in Dubai, United Arab Emirates, with a hybrid work arrangement that allows some work from home. The person in this role will design end-to-end data and AI architectures, including data pipelines, model deployment frameworks, and integration patterns that support enterprise-scale AI solutions. Day-to-day responsibilities include collaborating with stakeholders to understand business requirements, translating them into technical architectures, guiding software development teams, and ensuring solutions are secure, scalable, and maintainable. The role involves selecting appropriate tools and platforms, defining architectural standards and best practices, and overseeing integration with existing systems and cloud environments. The Data & AI Architect will also support project planning, provide technical leadership during delivery, and mentor team members on modern data, cloud, and AI engineering practices.Qualifications Strong Architecture and Architectural Design skills, including experience designing scalable data and AI solutions and enterprise systems.Hands-on Software Development experience in relevant languages and frameworks (e.g., Python, Java, cloud-native services) to guide implementation and review technical quality.Proficiency in Integration, including APIs, microservices, event-driven architectures, and connecting AI and data platforms to existing enterprise systems.Demonstrated Project Management capabilities, such as leading technical delivery, estimating effort, managing risks, and working in agile, cross-functional teams.Experience with data platforms and AI technologies (e.g., cloud data warehouses, data lakes, ML/AI platforms, MLOps, and model lifecycle management).Knowledge of major cloud providers (e.g., AWS, Azure, GCP) and their data and AI services, with the ability to design secure, cost-effective cloud architectures.Excellent communication and stakeholder management skills, with the ability to explain complex technical concepts to non-technical audiences.Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical