Principal Cloud & Systems Engineer, Radiology AI

ABOUT CUREMETRIX - is a global leader in Artificial Intelligence for medical imaging, committed to advancing technology that improves healthcare and survival rates across the globe. Its mission is to help save lives with early and more accurate detection and support improved clinical and financial outcomes, delivering technology that radiologists, healthcare systems, and patients can rely on with confidence.

If you want to be part of innovation that saves lives, take a giant step in your career, and put your hands-on experience to work in a successful start-up environment, we want you to join and grow with our team.

ROLE OVERVIEW

We are hiring a Principal Cloud & Systems Engineer to own the technical foundation of our radiology AI platform.

This is a true player–coach role — equal parts system-level architecture and hands-on engineering. You will define long-term technical direction and personally write production code, harden ML pipelines for clinical use, and lead resolution of complex distributed system failures.

You will shape a hybrid cloud platform that processes high-volume medical imaging workloads across hospital on-prem environments and AWS infrastructure — directly enabling radiologists to receive AI-powered insights faster and improving patient care.

What You’ll Own

Architecture & Platform Strategy

• End-to-end architecture of a distributed, hybrid cloud medical imaging platform
• Scalable patterns supporting tens → hundreds of healthcare deployments
• Compute platform decisions (Lambda, ECS/EKS, batch/parallel processing) backed by data and POCs
• Auto-scaling, cost optimization, reliability, and observability standards
• Major technical tradeoffs and long-term system evolution
• DICOM networking (DIMSE and DICOMweb) across diverse hospital environments — C-STORE, C-FIND, C-MOVE
• Implementation and maintenance of SCP/SCU services, routing logic, and transfer pipelines using utilities such as dcm4che, pynetdicom, dcmtk, Orthanc and similar tools

Infrastructure & Distributed Systems

• HIPAA-compliant hybrid cloud architectures
• Secure large-scale medical imaging data transfer between hospital systems and AWS
• Infrastructure-as-code strategy (Pulumi, Terraform, or equivalent)
• IAM, encryption, VPC/network segmentation
• Resilient backup, restore, and disaster recovery
• Deep troubleshooting across cloud, edge clients, GPU compute, and hospital IT networks

Hands-On Engineering (Player–Coach Execution)

• Design, implement, and review production backend and distributed processing systems
• Productize ML pipelines with Data Science
• Lead debugging of high-severity production incidents
• Optimize compute-intensive imaging workloads
• Raise the engineering bar through direct contribution and visible leadership
• Harden research code into clinical-grade software

Healthcare & Regulatory Alignment

• Lead technical onboarding and PACS integration strategy
• Design systems aligned with FDA medical device standards and HIPAA
• Collaborate with Quality on compliant SDLC documentation (SRS, SDS, validation, traceability)

What We’re Looking For

• 8+ years building and architecting production cloud systems
• 8+ years hands-on software engineering
• Prior Staff or Principal-level ownership preferred
• Strong Docker + Kubernetes experience
• Infrastructure-as-code proficiency
• Strong Python and/or Java in production environments
• Experience with distributed, event-driven systems
• Hybrid cloud / on-prem deployment experience
• Familiarity with DICOM, PACS, FHIR/HL7, and HIPAA-regulated environments
• Strong architectural instincts and sound engineering judgment across distributed systems, cloud-based micro-services, and event-driven pipelines
• Hands-on experience with cloud-native building blocks — object storage, message queues, pub/sub messaging, serverless compute, and container orchestration — across any major cloud provider (AWS Preferred)

Bonus: Medical imaging AI, GPU compute, LLM/RAG systems, or FDA-regulated software experience.

What Success Looks Like

• Platform scales predictably as customer deployments grow
• Production incidents decline in frequency and severity
• Engineering standards become measurable and consistent
• Deployment velocity increases without compromising compliance

This role is ideal for someone who wants real architectural ownership and is energized by building in a regulated, high-impact radiology AI environment.

If that’s you — let’s talk.