About the job
Imagen Technologies is building an AI-driven teleradiology practice, combining a vertically integrated medical group with an in-house AI development platform. With over $200 million in backing from Google Ventures and major clinical networks, the company is scaling quickly across the United States. Imagen’s platform, already serving millions of patients, is projected to expand from 22 states and 2.7 million patients in 2025 to more than 35 states and over 5 million patients annually by 2027.
The team has developed six FDA-cleared AI products focused on improving turnaround times and reducing diagnostic errors. Imagen is recognized as the fastest-growing teleradiology group in the country and aims to become one of the largest practices by 2026.
Role overview
This remote Engineering Manager, Data position centers on building and leading the AI Data Platform team at Imagen Technologies. The platform supports AI development for next-generation diagnostic tools, directly impacting patient care. The role involves both technical leadership and people management, with the expectation to transition fully into management as the team grows.
The Engineering Manager will report to the Head of Engineering and collaborate closely with the Chief AI Officer, product leaders, clinical teams, and engineers across the company.
What you will do
- Build and lead the team: Recruit, mentor, and develop a group of data engineers ranging from entry-level to mid-level. Set up team processes and foster a strong engineering culture from the start.
- Own the AI Data Platform: Take full technical and operational responsibility for the platform handling clinical imaging data and reports. Oversee ingestion, de-identification, transformation, and serving of data such as DICOM files, ensuring reliability, scalability, and security.
- Define and execute the technical roadmap: Set the direction for platform development. Prioritize scalability, new features, and technical debt in alignment with business goals.
- Ensure data quality and compliance: Build data quality frameworks, validation processes, and governance structures. Ensure all aspects of the platform comply with HIPAA and other relevant regulations.
- Drive cross-functional collaboration: Serve as the main point of contact for AI, product, clinical, and regulatory teams to maintain alignment and clear communication.

