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Leads platform projects crossing multiple teams, evolving runtimes or middleware patterns for interoperability and multi-tenant scale. Diagnoses and resolves complex cross-service issues; enforces versioning, compatibility, and safe rollout practices. Drives observability standards, capacity planning, and resilience patterns across several workloads. Produces migration guides and adoption playbooks that raise ecosystem consistency and developer experience.
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Lead the design and implementation of the AI-Assist platform, ensuring it is scalable, secure, and optimized for AI-driven applications.
Collaborate closely with the CDA team, including AI researchers, software developers, and healthcare domain experts, to define and refine the platform's architecture.
Develop and maintain the backend infrastructure, focusing on data ingestion, storage, processing, and retrieval systems.
Implement data modeling and database design to support complex healthcare data structures and relationships.
Integrate search technologies and natural language processing (NLP) capabilities to enable conversational search, semantic search, and summarization features.
Ensure data security and privacy by implementing access controls, encryption, and compliance with healthcare regulations.
Mentor and guide junior engineers, fostering a culture of knowledge-sharing and technical excellence.
Stay updated with the latest advancements in cloud-native AI/ML technologies and propose innovative solutions to enhance the CDA platform.
BS or MS degree in Computer Science or a related field is required, with a strong academic background.
6+ years of relevant software development experience, with a focus on backend and data-centric applications.
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.
Proficiency in Oracle Database and search technologies such as Opensearch, Pinecone, and Oracle Golden Gate Replication.
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.
Be part of a groundbreaking initiative to modernize and automate patient-centric healthcare globally.
Work with cutting-edge AI and cloud technologies, pushing the boundaries of what's possible in healthcare.
Enjoy a collaborative and dynamic team environment that values innovation and creativity.
Competitive compensation and benefits package, including professional development opportunities.
Make a meaningful impact on the lives of patients and healthcare providers worldwide.
Career Level - IC4
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