Oracle Health is seeking a Senior Manager, AI Engineering and Agent Platform to build and lead a new team focused on applying AI, LLMs, and agent-based software engineering to accelerate analytics and reporting delivery, improve data reliability, and unlock new insight generation capabilities across our analytics ecosystem.
This leader will be responsible for standing up a high-impact AI engineering function that designs and delivers production AI agents, agent tooling, semantic intelligence, and operational controls that integrate with existing analytics, data, and reporting platforms. The team’s mission is to serve as a force multiplier for existing engineering and analytics teams by automating repetitive work, improving trust in data, and enabling governed self-service and AI-assisted analytics experiences.
This role requires a technically strong engineering leader who can hire and lead a highly specialized team, define the roadmap and delivery model, and ensure solutions are scalable, secure, measurable, and aligned to Oracle Health business priorities. The ideal candidate combines deep engineering judgment with practical experience delivering enterprise AI capabilities into production.
Internal Responsibilities
- Build and lead a new AI engineering team focused on AI agents, LLM-enabled workflow automation, semantic intelligence, and AI platform capabilities.
- Define and execute the roadmap for AI-powered solutions that accelerate analytics development, reporting, insight generation, and data reliability.
- Partner with analytics, data engineering, application engineering, product, and business stakeholders to identify high-value use cases and drive adoption.
- Establish engineering standards for production AI systems, including evaluation, release management, governance, observability, and human-in-the-loop controls.
- Lead hiring, organizational design, coaching, performance management, and technical direction for a multidisciplinary AI team.
- Drive delivery of AI solutions such as data engineering agents, monitoring agents, metric design workflows, AI search, executive narrative generation, and insight discovery capabilities.
- Ensure AI solutions are secure, scalable, auditable, and aligned with Oracle Health operational and compliance expectations.
- Define measurable KPIs for team success, including cycle-time reduction, adoption, reliability, data quality improvement, and operational efficiency gains.
- Serve as the primary leader translating business needs into an executable AI engineering roadmap and production outcomes.
External Responsibilities
- Build and lead a new AI engineering team focused on AI agents, LLM-enabled workflow automation, semantic intelligence, and AI platform capabilities.
- Define and execute the roadmap for AI-powered solutions that accelerate analytics development, reporting, insight generation, and data reliability.
- Partner with analytics, data engineering, application engineering, product, and business stakeholders to identify high-value use cases and drive adoption.
- Establish engineering standards for production AI systems, including evaluation, release management, governance, observability, and human-in-the-loop controls.
- Lead hiring, organizational design, coaching, performance management, and technical direction for a multidisciplinary AI team.
- Drive delivery of AI solutions such as data engineering agents, monitoring agents, metric design workflows, AI search, executive narrative generation, and insight discovery capabilities.
- Ensure AI solutions are secure, scalable, auditable, and aligned with Oracle Health operational and compliance expectations.
- Define measurable KPIs for team success, including cycle-time reduction, adoption, reliability, data quality improvement, and operational efficiency gains.
- Serve as the primary leader translating business needs into an executable AI engineering roadmap and production outcomes.
