The AI Architect leads the design, development, and implementation of the AI strategy and solutions across the College. The AI Architect will be responsible for defining the overall architecture of AI systems, selecting appropriate technologies, ensuring scalability, security, and seamless integration with existing infrastructure. This role requires a deep understanding of AI principles, cloud computing, data architecture, and the ability to translate complex business requirements into robust and innovative AI solutions. The ideal candidate will possess strong technical leadership skills, excellent communication abilities, and a passion for driving transformative change through AI.

The potential minimum compensation for this position begins at $109,945.00 and is determined commensurate with education and experience.

Why work for Sinclair College?

The following are some of the benefits that professional staff with Sinclair College receive:

• Tuition waiver for employee and dependents for all Sinclair courses and programs
• Support for continued training and education, including tuition reimbursement for other universities and colleges
• OPERS pension participation option, with 14% employer contribution
• 4+ weeks of personal and vacation leave, 3+ weeks of sick leave annually
• 14 days of annually observed company holidays
• Expansive and competitive insurance programs, including an HSA with annual employer contribution available
• High quality programs and events for work-life balance

• AI Strategy and Vision: Define and drive the organization’s AI strategy, identifying key use cases, and aligning AI initiatives with overarching business goals
• Solution Architecture: Design the end-to-end architecture of AI systems, including data ingestion, storage, processing, model development, deployment, and integration with existing IT systems and networks
• Technology Evaluation and Selection: Evaluate and select appropriate AI/ML models, platforms, tools, and infrastructure based on performance, cost, scalability, security, and compliance requirements
• Scalability and Performance Optimization: Architect AI solutions that are highly scalable, performant, reliable, and cost-effective to meet current and future business needs
• Data Architecture and Governance: Collaborate with data engineering teams to define data architectures that support AI initiatives, ensuring data quality, security, and governance.
• Security and Compliance: Design AI systems with security and compliance considerations at the forefront, adhering to relevant industry standards and regulations.
• Integration and Interoperability: Ensure seamless integration of AI solutions with existing enterprise systems and data sources.
• Technical Leadership and Guidance: Provide technical leadership and guidance to data scientists, AI engineers, and other team members involved in the development and deployment of AI solutions.
• Stakeholder Communication: Effectively communicate the AI vision, strategy, and architectural blueprints to technical and non-technical stakeholders, including executive leadership.
• Research and Innovation: Stay abreast of the latest advancements in AI, machine learning, and related technologies, evaluating their potential impact and recommending innovative solutions.
• Best Practices and Standards: Define and enforce best practices, standards, and guidelines for AI development, deployment, and maintenance across the organization.

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