Chief Applied Scientist - AI & Agentic Systems

1w1 week ago

Oracle

US · Full-time · $161,700 – $338,500

About this role

Oracle Health is advancing how health happens with a human-centric experience powered by global data. We seek a highly technical Applied Scientist (IC6) to lead design and development of AI-powered agentic systems for healthcare and life sciences. This hands-on individual contributor role acts as player-coach, leading a small team of 3-5 engineers while building production systems.

Leverage generative AI, large language models, and advanced machine learning to automate complex workflows in population health, clinical data, and clinical trials. Build intelligent agentic systems for real-world use cases like clinical summarization and trial matching. Remain deeply hands-on with coding, system design, and deployment.

Join the Oracle Health Data Intelligence team redefining data and AI use in healthcare and life sciences. Build a cloud-first platform integrating clinical, research, and operational data for providers, pharma, and global systems. Focus on population health platforms, clinical trials, real-world evidence, and AI-driven insights.

This role suits those with healthcare or life sciences experience who have deployed AI/ML systems and agents in production. Transition from management to a high-impact IC position with technical leadership. Contribute to platforms accelerating drug development and improving patient outcomes globally.

Requirements

Experience in healthcare, population health, or life sciences domains
Built and deployed AI/ML systems and AI agents in production
Deeply hands-on with coding and system design
Experience leading small technical teams as player-coach
Expertise in generative AI, large language models, and advanced machine learning techniques
Knowledge of cloud-first platforms for clinical and research data integration

Responsibilities

Lead the design and implementation of end-to-end AI/ML systems from data ingestion to deployment
Architect and build AI agents and agentic workflows to automate complex healthcare and life sciences processes
Provide technical leadership to a small team of 3-5 engineers/scientists while remaining hands-on
Design and develop LLM-powered applications and AI agents for real-world healthcare use cases
Build intelligent systems for clinical summarization, documentation, chart review, and care plan generation
Develop systems for clinical trial matching, patient stratification, and population health analytics
Apply advanced techniques such as prompt engineering, fine-tuning, and RLHF to optimize model performance