Senior AI Architect, IT

Purpose: The Senior AI Architect position requires a high degree of technical expertise in at least 2 relevant domains such as AI solution development, data science, security, cloud, integrations, Healthcare IT or similar. As a Senior AI Architect, you will be challenged with aligning the AI strategy with the business strategy of multiple projects and/or department initiatives. You will lead the creation of best practices, policies, procedures, and other applicable AI documentation. You will collaborate with data scientists and other AI professionals to augment digital transformation efforts by identifying and piloting use cases. You will align technical implementation with existing and future requirements by gathering inputs from multiple stakeholders — business users, data scientists, security professionals, data engineers and analysts, and those in IT operations. Fully Remote Opportunity! Must be able to work eastern standard time. Responsibilities: The AI architect role spans the life cycle of AI solution development. The following paragraphs summarize the key responsibilities at each AI development stage.

• * Develop Business Case - The AI architect works with business stakeholders and business owners to develop the architecture needed and clearly define the outcomes and success metrics.
• Data Discovery - The AI architect must work with information/data architects, analytics team members and data scientists to identify and make available the data required. In addition, the AI architect must be sensitive to the data’s privacy, security and compliance issues.
• Model Selection- Depending on the business outcome sought, the AI solution development team will need to select the right foundation model to deliver the services needed. The AI architect will support the identification of the foundation model and ensure that it can address the needs of the business architecture.
• Model Training and Testing-The AI architect must work with stakeholders from across the IT organization to ensure that the right environment and computing resources are available for training and testing. This extends to ensuring that the data needed for testing and training is made available to the development team. The AI architect also supports the development of a training and testing plan, as well as the analysis of results and opportunities for improvement.
• Model Deployment- The AI architect will work with business and IT stakeholders to develop a roll-out plan for the AI solution.
• Continuous Monitoring- The AI architect will support the development of the monitoring plan and participate in the governance model if needed.

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