AI System Architect

Ideal candidate:

• A bachelor's or master's degree or certificates in computer science, artificial intelligence, or a related field is a must.
• Relevant work experience in AI system development, software engineering, or system architecture is highly valued.
• Solid understanding of various AI techniques, such as machine learning, deep learning, natural language processing, and computer vision. Must be familiar with different AI frameworks, libraries, and tools.
• Strong programming skills are essential, particularly in languages commonly used in AI development, such as Python, Java, or C++. Knowledge of other languages, such as R or MATLAB, can also be beneficial.
• AI system architects should be familiar with popular AI technologies and frameworks, such as TensorFlow, PyTorch, Keras, or scikit-learn. They should have hands-on experience in implementing AI models and systems using these tools.
• A deep understanding of system design principles, architecture patterns, and software engineering best practices is crucial.
• Knowledge of data management and processing techniques, including data ingestion, storage, preprocessing, and integration. Familiarity with big data technologies like Hadoop, Spark, or distributed computing frameworks is advantageous.
• Experience with cloud platforms, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform, is important.
• Strong problem-solving abilities and analytical thinking are crucial for an AI system architect.
• Effective communication skills are essential.
• Good to know : Power Automate, Power Apps and MsSQL optimization.

Responsibilities:

• The role of an AI system architect involves designing and developing the architecture and infrastructure for AI systems.
• AI system architects should be able to design scalable, efficient, and robust AI systems that meet the requirements of the specific use cases.
• AI system architects should be capable of deploying AI systems on the cloud, managing cloud resources, and optimizing performance and cost-efficiency.
• Must be able to identify and address technical challenges, optimize system performance, and make informed decisions based on data and analysis.
• Collaborate with cross-functional teams, including data scientists, software engineers, and stakeholders. Should be able to communicate complex technical concepts and ideas clearly and concisely.
• Given the rapid advancements in AI technologies, AI system architects should be proactive in staying updated with the latest trends, research, and industry developments. You should have a passion for learning and be willing to adapt to new tools and techniques.
• Our IT department is committed to providing support to all group companies, especially during times when the tasks and demands are not excessively demanding.