Director, AI Engineering & Operations

Posting Date

01/07/2026

2000 16th St, Denver, Colorado, 80202-5117, United States of America

The Director, AI Engineering & Operations will spearhead the development and execution of DaVita's AI strategy, ensuring alignment with business objectives and driving innovation across the organization.

They will lead a high-performing team of AI engineers, overseeing the entire AI lifecycle from data integration to model deployment and monitoring. This role requires a strategic thinker with a deep understanding of AI principles, excellent leadership skills, and a proven track record of successfully implementing AI solutions in complex environments.

This Director will lead the team responsible for design, delivery, and operation of AI/ML use cases, including A2A, ADK, MCP and Agentic AI. Leveraging enterprise tools including Google Cloud Platform (GCP), Google Vertex AI and Azure AI Foundry, ensuring reliability, security, governance and performance.

• Strategic Leadership: Develop and execute a comprehensive AI roadmap aligned with business goals. Identify key AI capabilities and prioritize projects based on business impact. Collaborate with executives to translate business needs into actionable AI strategies. Stay abreast of emerging AI technologies and trends, evaluating potential organizational impact. Make strategic decisions on building versus acquiring AI capabilities to meet current and future business needs.

• Technical Oversight: Oversee architecture and design for scalable AI systems and deployment frameworks. Provide technical guidance on AI model selection, optimization, and evaluation methodologies. Ensure responsible AI, quality standards, best practices, and ethical considerations are integrated into AI development. Guide AI development, model building, training, and implementation processes.

• Team Management: Lead and collaborate with a high-performing team of AI engineers, data scientists, and ML engineers. Foster a culture of innovation and continuous learning. Develop specialized AI talent within the organization. Delegate tasks effectively, manage project timelines, and monitor team performance.

• Project Execution: Oversee the full AI lifecycle from data integration to model deployment and monitoring. Collaborate with cross-functional teams to integrate AI solutions into existing systems. Manage project budgets, resource allocation, and delivery timelines. Ensure timely and successful implementation of AI initiatives.

• Operational Excellence: Oversee the establishment and execution of operational frameworks for AI initiatives across functions, ensuring seamless integration across business units.

• AI Best Practices & Guidelines: Establish organizational AI & Automation best practices and guidelines. Ensure quality, security, and regulatory compliance in all AI initiatives. Implement responsible AI principles throughout the development lifecycle.

• Collaboration and Communication: Collaborate with stakeholders and project managers to turn business goals into technical solutions. Work closely with internal stakeholders to champion AI initiatives, ensuring they are well-integrated with the company's strategic vision. Coordinating with development teams across the organization to integrate AI capabilities.

• Technical Guidance and Mentorship: Provide expert technical guidance, mentorship, and coaching to team members.

• Innovation and Incubation: Drive AI adoption, oversee capability development, and ensure successful integration of AI solutions across the organization. Track record of incubating emerging AI capabilities into structured, reusable offerings.

• Strategy and Roadmaps: Define and champion the vision, strategy, and roadmap for Data Engineering, Integrations, and AI Engineering Operations. Design and implement the long-term roadmap of technology architecture, engineering, development, and operations.

• Other Duties as Assigned

Education and Requirements:

Education:

• Masters’ in Computer Science, Artificial Intelligence, or related field with a strong focus on machine learning.

• A Bachelor's degree in Computer Science, Software Engineering, or a related field is also acceptable.

Experience:

• 10+ year