Generative AI Architect

Task and Responsibilities:

Solution Architect for Generative AI is responsible for designing, architecting, and development of AI product/service. The main responsibilities include:

• Designing, developing, and deploying Azure-based AI solutions, including machine learning models, cognitive services, and data analytics solutions.
• Collaborating with cross-functional teams, such as data scientists, business analysts, and developers, to design and implement AI solutions that meet business requirements.
• Building and training machine learning models using Azure Machine Learning, and tuning models for optimal performance.
• Developing and deploying custom AI models using Azure Cognitive Services, such as speech recognition, language understanding, and computer vision.
• Creating data pipelines to collect, process, and prepare data for analysis and modeling using Azure data services, such as Azure Data Factory and Azure Databricks.
• Implementing data analytics solutions using Azure Synapse Analytics or other Azure data services.
• Deploying and managing Azure services and resources using Azure DevOps or other deployment tools.
• Monitoring and troubleshooting deployed solutions to ensure optimal performance and reliability.
• Ensuring compliance with security and regulatory requirements related to AI solutions.
• Staying up-to-date with the latest Azure AI technologies and industry developments, and sharing knowledge and best practices with the team.

Qualifications:

• Overall 8+ years’ combined experience in IT and recent 5 years as AI engineer.
• Bachelor's or master's degree in computer science, information technology, or a related field.
• Experience in designing, developing, and delivering successful AI Services.
• Experience with cloud computing technologies, such Azure.
• Relevant industry certifications, such as Microsoft Certified: Azure AI Engineer, Azure Solution Architect etc. is a plus.
• Excellent written and verbal communication skills to collaborate with cross-functional teams and communicate technical information to non-technical stakeholders.