Azure AI Services Engineer @ SquareOne in SquareOne

Platform centers on the rapidly evolving realms of Artificial Intelligence (AI), focusing on enabling high-value AI use cases through fit-for-purpose platforms. At its core, Platform aims to establish a foundation for a Center of Excellence in AI and GenAI, an innovative hub bringing together leading AI experts. This is a place where best AI practices are shared and new ideas explored, all to reinforce our dedication to fostering innovation and excellence in support of Ten-Year Ambitions.

• Bachelor’s degree in Computer Science, Engineering, or related field; or equivalent experience.
• 5+ years of experience in Azure cloud engineering and architecture.
• Strong understanding of core Azure services.
• Proven experience with Azure AI services such as Azure Machine Learning, Cognitive Services, etc.
• Proficiency in infrastructure as code.
• Experience with containerization technologies like Docker and orchestration platforms like Kubernetes.
• Proficiency with CI/CD pipelines and tools.
• Solid understanding of networking concepts, security best practices, and cloud governance.
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Knowledge of DevOps practices.

Platform centers on the rapidly evolving realms of Artificial Intelligence (AI), focusing on enabling high-value AI use cases through fit-for-purpose platforms. At its core, Platform aims to establish a foundation for a Center of Excellence in AI and GenAI, an innovative hub bringing together leading AI experts. This is a place where best AI practices are shared and new ideas explored, all to reinforce our dedication to fostering innovation and excellence in support of Ten-Year Ambitions.

,[Design, develop, and manage robust and scalable Azure cloud infrastructure to support Platform., Implement and maintain AI/GenAI services using Azure AI services e.g. Azure OpenAI offerings., Collaborate with data scientists, MLOps Engineers, and developers to deploy AI services into production., Optimize cloud-based systems for performance, reliability, and cost-efficiency., Monitor and troubleshoot cloud infrastructure, ensuring high availability and security., Automate cloud operations and processes using automation tools., Stay up-to-date with the latest Azure services, best practices, and industry trends in AI/GenAI., Provide technical guidance and mentorship to team members on cloud and AI-related projects., Develop and maintain documentation for design specs, processes, and procedures., Develop infrastructure as code using Bicep., Maintain CI/CD pipelines for deployment and automatic testing of the infrastructure code.]
Requirements: Azure Cloud, Machine learning, Docker, Kubernetes, DevOps, Azure AI Services, Azure