We're tackling one of healthcare's most critical challenges in medical imaging and diagnostics. Our company operates at the intersection of cutting-edge AI and clinical practice, building technology that directly impacts patient outcomes. We've assembled one of the industry's most comprehensive and diverse medical imaging datasets and have a proven product-market fit with a substantial customer pipeline already in place.
We're seeking a strong generalist Software Engineer (Backend) to build the production systems and customer integrations that bring our models into clinical use at scale. On a lean engineering team, you'll wear several hats: designing and shipping backend services and APIs, building the networking and integration layer that connects us securely to customer hospital systems, standing up production data pipelines and CI/CD, and keeping all of it HIPAA-compliant. You'll work closely with the ML team, lending a hand on ML infrastructure when priorities demand, and you'll do well here if you like owning ambiguous, high-impact problems end to end.
Design, build, and operate backend services and APIs that deliver reliable end-to-end experiences from data ingestion through model output.
Build and maintain the integration layer connecting our applications to customer systems, including PACS, RIS, and EHRs, using medical communication protocols such as DICOM, DICOMweb, HL7, and FHIR.
Design reliable cloud networking for secure customer onboarding, including site-to-site VPNs and connectivity that scales to many external sites, and work directly with customer IT teams to bring each site online.
Build and operate production data pipelines and storage, spanning ETL, data lake, and data warehouse, handling hundreds of terabytes of imaging and clinical data.
Build CI/CD and deployment automation that lets a lean team ship quickly and safely.
Ensure systems handling PHI are HIPAA-compliant by design, with encryption, access controls, audit logging, and secure data handling throughout.
Build model inference pipelines for live and offline traffic, and support ML infrastructure alongside the ML team as needs arise.
Own large backend projects from design through deployment, leading technical design, driving quality through design reviews and testing, and helping set engineering best practices on a lean team.
5+ years as a software engineer, with a track record of delivering on time and at quality
Proficiency in a backend language (Go, Python, Java, or similar) and strong experience with cloud platforms and distributed architectures, particularly AWS
Strong experience designing and building backend infrastructure, including APIs, data pipelines, and services, that is reliable, scalable, and maintainable
Hands-on experience with schema design and data modeling
Experience building and integrating with external or third-party systems, including the networking and security concerns of connecting across organizational boundaries
Strong problem-solving skills and the ability to troubleshoot complex distributed systems
Experience shipping quickly under competing priorities, and comfort with the ambiguity of a lean team
Excellent communication skills and the ability to work cross-functionally with technical and non-technical stakeholders, including external customers and vendors
Experience with healthcare integration standards and imaging systems (DICOM, DICOMweb, HL7, FHIR, PACS/RIS, IHE profiles)
Experience building and operating HIPAA-compliant systems, or handling PHI and healthcare security requirements
Experience with secure network integration, such as site-to-site VPNs, private connectivity, and onboarding enterprise or hospital customers alongside their IT teams
Experience with CI/CD tooling and infrastructure-as-code (Terraform, Docker, Kubernetes)
Experience with large-scale ETL, data lake, or data warehouse systems
Experience contributing to ML infrastructure or model inference pipelines
Skills Required
- 5+ years as a software engineer
- Proficiency in a backend language (Go, Python, Java, or similar)
- Strong experience with cloud platforms and distributed architectures, particularly AWS
- Experience designing and building backend infrastructure (APIs, data pipelines, services)
- Hands-on experience with schema design and data modeling
- Experience building and integrating with external or third-party systems, including networking and security across organizational boundaries
- Strong problem-solving and troubleshooting skills for complex distributed systems
- Ability to ship quickly under competing priorities in a lean team
- Excellent communication skills and ability to work cross-functionally and with external customers/vendors
- Experience with healthcare integration standards and imaging systems (DICOM, DICOMweb, HL7, FHIR, PACS/RIS, IHE profiles)
- Experience building and operating HIPAA-compliant systems or handling PHI and healthcare security requirements
- Experience with secure network integration (site-to-site VPNs, private connectivity) and onboarding enterprise/hospital customers
- Experience with CI/CD tooling and infrastructure-as-code (Terraform, Docker, Kubernetes)
- Experience with large-scale ETL, data lake, or data warehouse systems
- Experience contributing to ML infrastructure or model inference pipelines
What We Do
Epsilon Health exists to solve the looming global radiology crisis before it reshapes patient care. Radiology underpins nearly every medical specialty, yet it is one of the most strained parts of the healthcare system. We’re rethinking how imaging and interpretation work to make radiology faster, more reliable, and future-proof.
