Full-Time AZURE AI Architect

Top Skills (not flexible): Great tenure in their positions, last role must be for at least 2 years and prior roles cannot be short-term, Azure and AI deep technical knowledge, Computer Science or Technical Degree form US School/US university.

Responsibilities
Design and implement scalable and secure AI-enabled cloud platforms that enhance developer experience (DX) and accelerate vertical solution delivery.
Ensure the security, scalability, reliability, and availability of cloud solutions, using cloud-native tools and services, such as Infrastructure-as-Code, Azure Monitor, Advance Threat Detection, Defender etc.
Integrate and deploy AI and machine learning models and frameworks, such as TensorFlow, PyTorch, MXNet, etc., using cloud-based platforms and services, such as Azure OpenAI Service, AI Search, Machine Learning Services, etc.
Introduce CI/CD pipelines that provide rapid feedback and allow continuous development and delivery.
Optimize and monitor the performance, cost, and efficiency of cloud solutions, using cloud-based tools and services, such as Azure Activity Log, Application Insights, Cost Management, etc.
Collaborate with other engineers, data scientists, product managers, and stakeholders to understand business needs and deliver high-quality cloud solutions.
Research and evaluate new technologies and best practices in AI and cloud computing and share knowledge and insights with the team.

Required Qualifications and Experience
Bachelor's degree in Computer Science, Engineering or other related scientific or technical discipline.
At least 15 years of experience in software engineering, with a focus on cloud development.
Proficient in one or more programing languages including Python, Java, C#, Angular, React.
5 or more years of experience with Azure.
3 or more years of experience in integrating and deploying AI and machine learning models and frameworks, using cloud-based platforms and services.
3 or more years of experience using AI and machine learning concepts and techniques, such as supervised learning, unsupervised learning, deep learning, natural language processing, computer vision, etc.

Preferred Qualifications and Experience
Previous experience as a hands-on CTO.
Full-stack development experience.
Experience in designing and implementing cloud architectures that support AI and machine learning applications, using cloud-native tools and services.
Experience in optimizing and monitoring the performance, cost, and efficiency of cloud solutions, using cloud-based tools and services.
Excellent communication, collaboration, and problem-solving skills.
Passion for learning and innovation.