Software Engineer – Backend (Advanced Medical Image Visualization)

AI overview

Work on high-performance backend systems for advanced medical image visualization, handling DICOM data and integrating AI inference, within a collaborative, expert-driven environment.

About the Role

We are looking for a Backend Software Engineer to build and scale high-performance backend systems that power advanced medical image visualization platforms. You will work on services handling DICOM/non-DICOM imaging data, metadata orchestration, real-time image streaming, AI inference integration, and enterprise healthcare workflows across PACS, VNA, and Enterprise Viewers.

This role sits at the intersection of distributed systems, medical imaging, cloud infrastructure, and performance-critical backend engineering.

Key Responsibilities

Core Backend Engineering

  • Design, develop, and maintain scalable backend services for medical image ingestion, retrieval, processing, and visualization.

  • Build low-latency APIs for image access, study orchestration, annotations, and viewer interactions.

  • Optimize backend systems for high throughput, large data volumes (TBs–PBs), and sub-second response times.

Medical Imaging & Visualization

  • Implement backend workflows for DICOM (C-STORE, C-FIND, C-MOVE, C-GET, WADO-RS, QIDO-RS, STOW-RS).

  • Support advanced visualization use cases: 2D/3D/MPR, cine playback, volumetric rendering, and image fusion.

  • Manage image metadata, series relationships, and study lifecycle across PACS, VNA, and Enterprise Viewer ecosystems.

  • Enable backend services for GSPS, SR, annotations, measurements, and overlays.

Cloud & Distributed Systems

  • Architect microservices-based systems using REST/gRPC/event-driven patterns.

  • Handle object storage (S3/GCS/Azure Blob) for imaging data and metadata persistence.

  • Implement caching, asynchronous processing, and background pipelines for image workflows.

  • Ensure fault tolerance, high availability, and disaster recovery.

AI & Advanced Capabilities

  • Integrate backend services with AI/ML inference pipelines (e.g., triage, detection, quantification).

  • Support AI result persistence, versioning, explainability metadata, and viewer overlays.

  • Enable orchestration between imaging data and AI models at scale.

Security, Compliance & Quality

  • Implement security, access control, audit logging, and data isolation.

  • Ensure compliance with HIPAA, GDPR, ISO 13485 / 62304 where applicable.

  • Write unit, integration, and performance tests; support CI/CD pipelines.

  • Participate in architecture reviews, code reviews, and technical documentation.

Requirements

Backend & Systems

  • Strong proficiency in Java / Kotlin / C++ / Python / Go (any one primary, others a plus).

  • Experience with RESTful APIs, gRPC, message queues (Kafka, RabbitMQ, Pub/Sub).

  • Solid understanding of distributed systems, concurrency, memory management, and performance tuning.

  • Experience with relational (PostgreSQL/MySQL) and NoSQL (MongoDB, Redis, Elasticsearch) databases.

Medical Imaging (Must-Have or Strong Plus)

  • Hands-on experience with DICOM standards and imaging workflows.

  • Familiarity with PACS, VNA, RIS integrations, or healthcare imaging platforms.

  • Understanding of image formats, compression (JPEG2000), pixel data handling, and metadata models.

Cloud & DevOps

  • Experience deploying backend services on AWS / GCP / Azure.

  • Working knowledge of Docker, Kubernetes, CI/CD pipelines.

  • Experience with observability (logs, metrics, tracing).

Good to Have (Differentiators)

  • Experience with high-performance image streaming or tile-based rendering backends.

  • Knowledge of 3D visualization pipelines, volume rendering, or GPU-assisted workflows.

  • Exposure to HL7 / FHIR integrations.

  • Experience building multi-tenant SaaS healthcare platforms.

  • Prior work in regulated medical device software environments.

    What We Offer

    • Opportunity to work on cutting-edge medical imaging and AI platforms used by clinicians globally.

    • Ownership of mission-critical, high-scale backend systems.

    • Collaborative environment with imaging, AI, and clinical domain experts.

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