About Gleamer

Gleamer develops an AI copilot for radiologists , helping healthcare professionals detect pathologies across X-ray, CT, MRI, and Tomosynthesis. Our CE-marked and FDA-cleared solutions are deployed in hospitals across the world.

As we expand our platform, we are looking for a Software Architect to design the scalable infrastructure that will bring Gleamer’s technology to a broader range of healthcare use cases — extending our impact beyond the medical AI algorithm itself.

The Role

You will be responsible for designing and evolving Gleamer’s core architecture for performance, reliability, and clinical-grade scalability. You’ll collaborate closely with the CTO, engineering leads, and clinical partners to ensure our systems integrate seamlessly into existing imaging workflows while supporting future AI-driven services.

Key Responsibilities

• Define and evolve the end-to-end architecture of Gleamer’s platform to support large-scale AI medical imaging workloads.
• Design distributed, cloud-native systems using microservices , event-driven patterns , and container orchestration .
• Oversee data and API integrations with PACS, RIS, DICOM Viewers , and hospital environments.
• Ensure system scalability, compliance, and robustness in production healthcare settings.
• Work cross-functionally with AI, product, and platform teams to transform complex requirements into sustainable architectures.
• Mentor engineers and contribute to engineering excellence and best practices across teams.

Required Experience & Skills

• 10+ years in software engineering, with strong background in system architecture and cloud infrastructure .
• 4+ years in medical imaging , ideally with hands-on experience in PACS, DICOM Viewers, or healthcare IT systems .
• Proven experience working in a scale-up environment , designing and scaling distributed systems.
• Expertise in:
• Cloud platforms: GCP (preferred, AWS and Azure ok)
• Microservices and distributed systems design
• Event-driven architectures and queueing systems (Pubsub, RabbitMQ, etc.)
• Containerization and orchestration: Docker & Kubernetes (required)
• One or more of the following programming languages: Java, Python, Go, Rust
• Solid understanding of DICOM, HL7, FHIR , and clinical interoperability standards.
• Experience deploying AI/ML models in clinical-grade production systems is a plus.

Soft Skills

• Excellent communication and stakeholder management abilities.
• Fluent in French and English (spoken and written).
• Comfortable managing complex, multi-stakeholder projects in regulated healthcare environments.