Chief Applied Scientist – AI & Agentic Systems (Healthcare & Life Sciences)
Oracle · United States
- Hybrid
- Full-time
- $250,000 / year
- United States
Job highlights
- Lead AI agentic systems development for healthcare.
- Hands-on technical leadership for a small team.
- Utilize generative AI and LLMs for automation.
- Develop solutions for clinical trials and patient outcomes.
- Work with diverse healthcare and life sciences data.
About the role
About Oracle Health
Oracle Health is on a bold journey to advance how health happens by creating a human-centric experience powered by global data. Our mission is to support clinicians, empower patients, and fuel innovation that saves lives. As part of this transformation, Oracle Health is expanding into Life Sciences and Clinical Trials, building next-generation platforms that accelerate drug development, enable real-world evidence, and improve patient outcomes globally.About The Team
The Oracle Health Data Intelligence (HDI) team is redefining how healthcare and life sciences organizations use data and AI to drive innovation. We are building a cloud-first platform that integrates clinical, research, and operational data to power insights across healthcare providers, pharmaceutical companies, and global health systems. Our focus areas include:- Population health and clinical data platforms
- Clinical trials and life sciences innovation
- Real-world evidence and safety analytics
- AI-driven insights and intelligent agentic systems
Role Overview
We are seeking a highly technical Applied Scientist (IC6) to lead the design and development of AI-powered agentic systems for healthcare and life sciences. This is a hands-on individual contributor role with technical leadership responsibilities. You will operate as a player-coach, leading a small team (3–5 engineers/scientists) while actively building and deploying production-grade AI systems. You will leverage generative AI, large language models (LLMs), and advanced machine learning techniques to create intelligent systems that automate complex workflows across population health, clinical data, and clinical trials. This role is ideal for someone who:- Has experience in healthcare, population health, or life sciences domains
- Has built and deployed AI/ML systems and AI agents in production
- Enjoys being deeply hands-on with coding and system design
- May be a current or former manager who wants to return to a high-impact IC role
Key Responsibilities
Technical Leadership & Ownership
- 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 (3–5), driving execution while remaining hands-on
Generative AI & Agentic Systems
- Design and develop LLM-powered applications and AI agents for real-world healthcare use cases
- Build intelligent systems for workflows such as: Clinical summarization and documentation, Chart review and care plan generation, Clinical trial matching and patient stratification, Population health analytics and quality measurement
- Apply advanced techniques such as prompt engineering, fine-tuning, and RLHF to optimize model performance
Healthcare & Life Sciences Solutions
- Work with clinical, population health, and life sciences datasets (EHR, claims, research data)
- Translate domain requirements into scalable AI solutions for: Clinical trials and safety monitoring, Real-world evidence generation, Value-based care and outcomes analysis
- Ensure solutions align with healthcare regulations and compliance standards (e.g., HIPAA, HITRUST)
Scalable System Development
- Build and maintain scalable data pipelines and AI infrastructure
- Integrate structured and unstructured data into AI/ML systems
- Deploy solutions in cloud environments (OCI, AWS, Azure, or GCP) with a focus on reliability and performance
Cross-Functional Collaboration
- Partner with engineering, product, and domain experts to deliver impactful solutions
- Act as a bridge between technical teams and healthcare/life sciences stakeholders
- Drive adoption of AI solutions in clinical and operational workflows
Innovation & Mentorship
- Stay at the forefront of AI, LLMs, and agentic system advancements
- Mentor team members and contribute to a culture of technical excellence
- Influence the direction of AI innovation within Oracle Health
Basic Qualifications
- 10+ years of experience in AI/ML, applied science, or related technical roles
- Proven experience building and deploying production-grade AI/ML systems
- Strong hands-on programming skills (e.g., Python, Java, or C++)
- Experience designing or implementing AI agents or agentic workflows
- Experience leading end-to-end system design and delivery
Preferred Qualifications
- Domain expertise in: Population Health, Clinical Data / EHR systems, Life Sciences / Clinical Trials
- Experience with organizations or platforms such as: Epic, Innovaccer, Acadia, Truveta, IQVIA
- Expertise in Generative AI and LLM frameworks (e.g., GPT, transformer-based models)
- Experience with: PyTorch, TensorFlow, Hugging Face Transformers
- Multi-modal data (text, imaging, structured data)
- Distributed systems and large-scale data processing
- Knowledge of healthcare standards (FHIR, HL7)
- Experience working in regulated environments (HIPAA, HITRUST)
- Prior experience leading small teams while remaining hands-on
What We’re Looking For
A builder and problem solver who can go from concept to production. Strong ownership and ability to operate in ambiguous, fast-paced environments. Deep curiosity about applying AI to real-world healthcare challenges. Ability to balance technical depth, domain knowledge, and leadership.Why Join Us
- Work on cutting-edge AI and agentic systems in healthcare and life sciences
- Help shape Oracle Health’s next-generation AI platform
- Direct impact on patient outcomes and clinical innovation
- Collaborate with world-class engineers, scientists, and healthcare experts
Qualifications Disclaimer
Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates. Range and benefit information provided in this posting are specific to the stated locations only.Key skills/competency
- Chief Applied Scientist
- AI & Agentic Systems
- Healthcare & Life Sciences
- Generative AI
- Large Language Models (LLMs)
- Machine Learning
- Python
- Cloud Computing
- Technical Leadership
- System Design
Skills & topics
- Chief Applied Scientist
- AI
- Agentic Systems
- Healthcare
- Life Sciences
- Generative AI
- LLM
- Machine Learning
- Python
- Cloud Computing
- Technical Leadership
- System Design
- Oracle Health
- Clinical Trials
- Population Health
How to get hired
- Tailor your resume: Highlight AI/ML, agentic systems, and healthcare domain experience. Quantify achievements.
- Showcase leadership: Emphasize technical leadership, team mentorship, and end-to-end system delivery.
- Demonstrate technical skills: Detail experience with Python, LLMs, generative AI, and cloud platforms.
- Understand the domain: Articulate your knowledge of healthcare, clinical trials, or life sciences.
- Prepare for technical interviews: Expect deep dives into AI/ML concepts, system design, and coding challenges.
Technical preparation
Master Python for ML and AI development.,Study LLM architectures and prompt engineering.,Practice building and deploying AI agents.,Review cloud platform AI/ML services.
Behavioral questions
Describe leading technical projects with teams.,How do you handle ambiguity in fast-paced environments?,Share an experience applying AI to healthcare.,How do you balance technical depth and leadership?
Frequently asked questions
- What specific AI technologies are central to the Chief Applied Scientist role at Oracle Health?
- The Chief Applied Scientist role at Oracle Health heavily utilizes Generative AI, Large Language Models (LLMs), and advanced machine learning techniques. You'll be designing and developing AI agents and agentic workflows, applying methods like prompt engineering, fine-tuning, and Reinforcement Learning from Human Feedback (RLHF) to optimize performance for healthcare and life sciences applications.
- What kind of impact can I expect to make as a Chief Applied Scientist at Oracle Health?
- As a Chief Applied Scientist at Oracle Health, you will directly impact patient outcomes and clinical innovation by helping to shape the company's next-generation AI platform. Your work will involve automating complex workflows in areas like clinical summarization, trial matching, and population health analytics, driving advancements in drug development and healthcare delivery.
- Is this Chief Applied Scientist role hands-on or more management-focused?
- This Chief Applied Scientist role is a 'player-coach' position, meaning it's a hands-on individual contributor role with technical leadership responsibilities. You will lead a small team of 3-5 engineers/scientists, actively contributing to coding and system design while guiding the team's execution.
- What domain expertise is most valuable for this Chief Applied Scientist position?
- The most valuable domain expertise for this Chief Applied Scientist role includes experience in healthcare, population health, or life sciences. Specifically, familiarity with clinical data (EHRs), clinical trials, real-world evidence generation, and regulated healthcare environments (HIPAA, HITRUST) is highly preferred.
- How important are cloud deployment skills for the Chief Applied Scientist role at Oracle Health?
- Cloud deployment skills are critical. You will be responsible for building and maintaining scalable data pipelines and AI infrastructure, deploying solutions in cloud environments like OCI, AWS, Azure, or GCP. A focus on reliability and performance in these deployments is essential for the success of the AI systems.
- What are the key differences between the 'Basic Qualifications' and 'Preferred Qualifications' for this role?
- The 'Basic Qualifications' outline the minimum requirements, such as 10+ years in AI/ML, experience building production AI systems, strong programming skills (Python), and experience with AI agents. The 'Preferred Qualifications' list desirable, but not strictly mandatory, skills and experiences, including specific healthcare domain expertise, familiarity with certain platforms (Epic, IQVIA), advanced LLM framework experience (PyTorch, TensorFlow), and knowledge of healthcare standards (FHIR, HL7).