As a Principal Member of Technical Staff, you will be a key contributor to the development and success of our next-generation Healthcare Agents, which leverages the power of generative AI and cloud-native technologies. Your expertise in data platform engineering and service development will drive the creation of a robust and intelligent system, enhancing the healthcare experience for patients and clinicians alike.
Internal Responsibilities
Responsibilities:
- Lead the strategy, design, and implementation of the Agentic AI workflows, shaping scalable, secure, and AI-optimized architecture across teams and LOB priorities with meaningful impact on Oracle Health outcomes.
- Serve as a recognized subject matter expert for agentic AI, healthcare data platforms, search/NLP, and cloud-native backend architecture; translate industry practices into durable platform standards and reusable patterns.
- Influence and align AI researchers, healthcare domain experts, product, security, operations, and LOB leadership to define roadmaps, resolve architectural tradeoffs, and drive cross-functional execution.
- Own and continuously improve platform capabilities for data ingestion, storage, processing, retrieval, conversational search, semantic search, summarization, and AI-driven healthcare workflows.
- Drive complex and ambiguous architecture and implementation decisions where analysis of data, performance, privacy, security, and healthcare constraints requires evaluation of intangibles.
- Advise leadership on platform strategy, operational readiness, data security, privacy, access controls, encryption, and healthcare regulatory compliance.
- Mentor and guide engineers across teams; build technical depth through design reviews, knowledge-sharing, reference implementations, and coaching that uplifts peers beyond the immediate team.
- Use customer and market understanding to shape platform propositions, identify opportunities, and deliver competitive advantage for Oracle Health and its customers.
Qualifications:
- BS or MS degree in Computer Science or a related field is required, with a strong academic background.
- 6-10+ years of relevant software development experience, with a focus on backend and data-centric applications with a leadership focus preferred
- Hands-on experience building AI/ML or generative AI applications, including LLM-powered workflows, agentic systems, prompt engineering, and tool/function calling.
- Proficient in Java, Python, or similar object-oriented languages for building robust backend systems.
- Strong software engineering fundamentals, including expertise in data structures, algorithms, RESTful services, and microservices architecture.
- Hands-on experience with cloud-native development on major cloud platforms (OCI, Azure, GCP, AWS) is essential.
- In-depth knowledge of data architecture, including database design, data modeling, analytics, metadata management, and data-access controls.
- Experience with data pipeline orchestration using tools like Kafka, Flink, and RabbitMQ.
- Understanding of system design and distributed systems architecture best practices.
- Familiarity with cloud engineering infrastructure and containerization (Kubernetes, Docker).
- Excellent communication skills for conveying complex technical concepts to both technical and non-technical stakeholders.
- Demonstrated technical leadership and a passion for mentoring junior team members.
External Responsibilities
Responsibilities:
- Lead the strategy, design, and implementation of the Agentic AI workflows, shaping scalable, secure, and AI-optimized architecture across teams and LOB priorities with meaningful impact on Oracle Health outcomes.
- Serve as a recognized subject matter expert for agentic AI, healthcare data platforms, search/NLP, and cloud-native backend architecture; translate industry practices into durable platform standards and reusable patterns.
- Influence and align AI researchers, healthcare domain experts, product, security, operations, and LOB leadership to define roadmaps, resolve architectural tradeoffs, and drive cross-functional execution.
- Own and continuously improve platform capabilities for data ingestion, storage, processing, retrieval, conversational search, semantic search, summarization, and AI-driven healthcare workflows.
- Drive complex and ambiguous architecture and implementation decisions where analysis of data, performance, privacy, security, and healthcare constraints requires evaluation of intangibles.
- Advise leadership on platform strategy, operational readiness, data security, privacy, access controls, encryption, and healthcare regulatory compliance.
- Mentor and guide engineers across teams; build technical depth through design reviews, knowledge-sharing, reference implementations, and coaching that uplifts peers beyond the immediate team.
- Use customer and market understanding to shape platform propositions, identify opportunities, and deliver competitive advantage for Oracle Health and its customers.
Qualifications:
- BS or MS degree in Computer Science or a related field is required, with a strong academic background.
- 6-10+ years of relevant software development experience, with a focus on backend and data-centric applications with a leadership focus preferred
- Hands-on experience building AI/ML or generative AI applications, including LLM-powered workflows, agentic systems, prompt engineering, and tool/function calling.
- Proficient in Java, Python, or similar object-oriented languages for building robust backend systems.
- Strong software engineering fundamentals, including expertise in data structures, algorithms, RESTful services, and microservices architecture.
- Hands-on experience with cloud-native development on major cloud platforms (OCI, Azure, GCP, AWS) is essential.
- In-depth knowledge of data architecture, including database design, data modeling, analytics, metadata management, and data-access controls.
- Experience with data pipeline orchestration using tools like Kafka, Flink, and RabbitMQ.
- Understanding of system design and distributed systems architecture best practices.
- Familiarity with cloud engineering infrastructure and containerization (Kubernetes, Docker).
- Excellent communication skills for conveying complex technical concepts to both technical and non-technical stakeholders.
- Demonstrated technical leadership and a passion for mentoring junior team members.
