Job Description

Brief Summary

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Oracle Health & AI delivers a versatile, no-code platform designed to facilitate the creation, deployment, and operation of enterprise-scale integrations across both cloud and on-premises environments, as well as diverse information systems. By incorporating FHIR standards for healthcare data and harnessing advanced AI/ML features, including large language models (LLMs), pre-built accelerators, and workflow automation, Oracle significantly streamlines and modernizes healthcare applications.

Team and Product Description :

Oracle Health and AI (OHAI) is a cloud-managed service that operates natively on Oracle Cloud Infrastructure (OCI). OHAI facilitates connectivity with various data sources, including healthcare systems adhering to the FHIR (Fast Healthcare Interoperability Resources) standard. This service seamlessly integrates with both Oracle and non-Oracle SaaS applications, enterprise applications, databases, messaging systems, and diverse protocols such as REST, SOAP, OData, FTP, GraphQL, MLLP, and JDBC, across public, private, and on-premises networks.


In this role, you will collaborate closely with Oracle Health's healthcare systems, leveraging FHIR mappings and advanced AI/LLM capabilities to ensure the seamless integration of clinical data with enterprise applications. This supports decision-making and predictive analytics in healthcare. The development team is responsible for requirements gathering, system design, architecture, implementation, and support for cloud-native integrations, including FHIR-based applications and LLM-driven services. Our team is dedicated to enhancing healthcare interoperability, tackling data and application integration challenges to create a superior and seamless experience.

Description of the Role :

Design and develop cloud-native enterprise software products and services, focusing on distributed, scalable, fault-tolerant, and multi-tenant cloud services for healthcare applications using FHIR and LLM-based models for natural language processing (NLP). Build FHIR-compliant integrations with Oracle Health's healthcare data systems, ensuring adherence to FHIR standards in data exchange, patient record management, and clinical workflows, while integrating LLMs to provide contextual insights and automated processing of clinical data. Develop healthcare cloud applications following microservices and twelve-factor application principles, optimizing for data integration with FHIR-based services and LLMs for advanced text-based analysis and healthcare recommendations. Focus on API-first design using OpenAPI, Swagger, and test-driven development, ensuring integration with FHIR-based healthcare data through RESTful APIs, and leveraging LLMs for real-time patient data analytics. Code in Java, leveraging RESTful APIs, microservices, Docker, and Kubernetes, with integration into healthcare data systems at Oracle Health that use FHIR, and incorporating LLMs for scalable NLP tasks, such as summarizing patient information or automating documentation. Work with prominent healthcare APIs and other systems like AWS, Microsoft Azure, GCP, and Salesforce to facilitate healthcare data exchange, with programming languages like Java, Go, Python, JavaScript, and NodeJS, integrating AI-driven solutions and LLMs for intelligent data extraction. Implement message interchange formats such as JSON/JSON Schema, XML, Avro, and FHIR resources, while integrating LLM-based AI models to enhance decision-making, predictive analytics, and patient engagement. Collaborate with JavaScript frameworks like OJET, ReactJS, and AngularJS to create dynamic, healthcare-driven user interfaces, integrating with FHIR-based patient data systems and enhancing user experience with LLM-driven insights and contextual support. Provide technical evaluations, optimize applications, and implement best practices in developing cloud-native healthcare applications with FHIR and LLM capabilities for Oracle Health. Create reusable solutions that can accelerate the creation of healthcare applications using FHIR and LLMs, streamlining the integration with EHR and clinical systems, and delivering smarter healthcare insights.

Preferred Qualifications :

B.E./B.Tech/M.S./M.Tech in Computer Science. 3+ years of experience in cloud service development. Experience with LLMs, natural language processing (NLP), and integrating AI models into enterprise applications. Knowledge of healthcare standards like FHIR and experience in integrating healthcare data across enterprise applications would be beneficial. Strong ability to innovate and excel in a fast-paced environment, especially in the healthcare, AI, and cloud integration space. In this role, you'll be contributing to healthcare innovation at Oracle Health, focusing on integrating critical clinical data using FHIR, while leveraging LLM-based AI solutions and the power of Oracle Cloud Infrastructure to drive scalable and reliable healthcare solutions.

The role involves designing, developing, and operating scalable, multi-tenant cloud services on Oracle Cloud Infrastructure (OCI) for Oracle Health & AI, with a focus on integrating healthcare systems using FHIR standards. You will build cloud-native applications and FHIR-compliant integrations, ensuring smooth data exchange in clinical workflows. Leveraging large language models (LLMs) and AI-driven solutions, you'll enhance decision-making, predictive analytics, and automate healthcare processes. Responsibilities include API development, microservices architecture, and working with RESTful APIs and various data formats. You'll collaborate with teams to create reusable, FHIR-based solutions, focusing on healthcare interoperability and AI integration. Experience with cloud platforms, FHIR, and LLMs is preferred.

Key Responsibilities:

Design and Development: Create and implement scalable, multi-tenant cloud services on Oracle Cloud Infrastructure (OCI) tailored for Oracle Health. Integration: Develop and integrate healthcare systems using FHIR standards to ensure smooth data exchange in clinical workflows. Cloud-Native Applications: Build cloud-native applications and ensure compliance with FHIR standards for healthcare integrations. Decision-Making and Analytics: Leverage large language models (LLMs) and AI-driven solutions to enhance decision-making processes, predictive analytics, and automation in healthcare. API Development: Design and develop RESTful APIs to facilitate seamless integration and interaction with various healthcare data formats. Microservices Architecture: Implement and maintain a robust microservices architecture to support scalable and efficient cloud services. Collaborative Efforts: Work closely with cross-functional teams to create reusable, FHIR-based solutions focusing on healthcare interoperability and AI integration. Operational Excellence: Monitor, operate, and maintain cloud services to ensure optimal performance, reliability, and scalability. * Compliance and Standards: Ensure all cloud services and integrations comply with industry standards and regulations, particularly in healthcare.