Software Engineer, Clinical AI Devices

DeepHealth

1d•$60,000 - $80,000•Hybrid

About The Position

In the Clinical AI Devices team, the Software Engineer is primarily responsible for building and maintaining software in the Clinical AI domain, from wrapping deep learning models into containerized medical devices, to integration with other systems. This work spans all of the company's medical devices, across the main radiology modalities: X-Ray, CT, MRI, and Mammography. The focus of the current role is at the interface between product logic and the underlying serving platform, ensuring that requests are correctly validated, routed, and that results are properly assembled and returned.

Requirements

Bachelor's or Master’s Degree in a related field such as computer science, biomedical engineering or similar (required).
At least 5 years of experience in a similar or related relevant role
At least 5 years of experience working with Java, with proficiency in Spring Boot (required).
Fluent in English (required).
Accustomed to CI/CD practice (required).
Familiar with test-driven development and testing frameworks like JUnit (required).
Experience working with docker, cloud platforms such as GCP or AWS, and Kubernetes (required).

Nice To Haves

Experience working with Agentic Coding tools like Claude and Cursor (preferred).
Experience working with microservices and distributed systems (preferred).
Experience in the MedTech field, e.g. working with DICOM data, AI algorithms, and clinical workflows (preferred).

Responsibilities

Participate in the software development process: design, refine, and develop new features, and maintain existing ones.
Write code, review teammates' code, and contribute to the testing framework through automated and manual tests.
Work with the team lead and product manager to refine requirements.
Own features and projects end-to-end, from refinement to production.
Flag risks and bugs by keeping the radiologist's workflow in mind.
Support service and delivery teams with production issues.
Ensure compliance with Quality and Regulatory requirements throughout the development cycle, including technical documentation (e.g. implementation specs), cybersecurity processes, and risk analysis.
Collaborate with the team on strategic recommendations and improvements to technology and business.