Julian Jee
Chief Technology Officer, AIRS Medical
Julian Jee is available for media interviews, podcasts and speaking engagements on healthcare AI infrastructure, medical AI deployment, cloud and on-premise architecture, cybersecurity, platform scalability, engineering for regulated healthcare environments and the technology behind enterprise medical imaging AI.
About Julian Jee
Julian Jee is Chief Technology Officer of AIRS Medical, where he leads the technology and engineering foundation behind the company’s AI-powered MRI platform.
Julian joined AIRS Medical as SwiftMR® was making the transition from research into a commercial product. He built the engineering foundation required to take that technology from an emerging AI application to a platform capable of operating across real-world healthcare environments at scale.
Today, he architects and operates the infrastructure behind AIRS Medical’s technology across a hybrid of public cloud and hospital on-premise environments. The platform now spans more than nine regions and is engineered to scale globally while meeting the security, reliability and compliance requirements of regulated healthcare AI. That includes everything from multi-region cloud architecture to isolated on-premise deployments inside hospital networks, all delivered by a deliberately lean engineering team.
His approach to systems design is grounded in an unusually rigorous mathematical background. A three-time consecutive gold medalist at the Korean Mathematical Olympiad, Julian went on to study electrical engineering at Seoul National University. He applies that same discipline to distributed infrastructure, platform architecture, identity and access management, observability, security and the operational challenges of deploying AI inside healthcare systems.
Before joining AIRS Medical, Julian spent six years as a startup co-founder and CTO, building technology across very different environments, from parametric architectural-design software and mobile communications to automated Ethereum mining using idle computing capacity in internet cafés. He was a co-founder of Natasha and Smart Miner and later served as Team Lead at Hodoo AI Lab.
At AIRS Medical, Julian’s work sits at the intersection of AI, infrastructure and healthcare delivery: building the technology foundation that allows medical AI to move beyond a model or algorithm and function reliably inside hospitals around the world.
Why interview Julian
Julian brings a rare combination of deep technical rigor and real-world experience building healthcare AI infrastructure at scale. He can speak to what it actually takes to move medical AI from research into production, and keep it secure, reliable and operational across complex hospital environments.
Suggested discussion topics
Why medical AI must operate across very different technical environments, and how to architect for both.
Designing infrastructure that can support geographic expansion, healthcare regulation and different hospital environments.
Building identity, access, monitoring and security into the platform rather than treating them as deployment afterthoughts.
How scalable technology architecture enables solutions such as SwiftMR and the broader evolution toward MRI intelligence.
How architectural discipline, automation and platform thinking can allow lean teams to operate complex global infrastructure.
Media and speaking inquiries
Julian is available for interviews, expert commentary, panels and speaking engagements on the technology required to deploy and scale AI in healthcare.
Relevant topics include healthcare AI infrastructure, scaling medical AI from research to production, hybrid cloud and on-premise deployment, cybersecurity and identity in regulated healthcare environments, platform architecture, observability and reliability, enterprise medical imaging AI, global scalability, and building lean engineering teams for complex clinical technology platforms.
Politics, religion and unrelated controversial topics are outside the scope of available interviews and speaking engagements.
