Responsibilities:

Design and implementation of managing application settings across different environment, ensuring it is scalable, secure, and optimized for AI-driven applications. Collaborate closely with cross functional teams, 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. Experience building RESTful or gRPC services; API design, pagination, error handling, and observability. Define and develop software for tasks associated with the developing, debugging or designing of software applications or operating systems. Mentor and guide junior engineers, fostering a culture of knowledge-sharing and technical excellence. Provide technical leadership to other software developers. Specify, design and implement changes to existing software architecture to meet changing needs. Stay updated with the latest advancements in cloud-native AI/ML technologies and propose innovative solutions to enhance our platforms. 

Qualifications:

 

BS or MS degree in Computer Science or a related field is required, with a strong academic background. Must be U.S. citizen and be able to obtain a security clearance once hired 2+ 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. 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.