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Alexander K. React, AWS and Healthcare Platforms

My name is Alexander K. and I have over 5 years of experience in the tech industry. I specialize in the following technologies: React, Docker, JavaScript, Next.js, Amazon Web Services, etc.. I hold a degree in Master of Science (MS). Some of the notable projects I’ve worked on include: Scalable DICOM Routing & PACS Modernization Platform, Cloud PACS Deployment with Orthanc & OHIF, Distributed DICOM Microservices Platform, ETL Platform for Healthcare Stats, Medical Image AI Platform, etc.. I am based in Siheung-dong, South Korea. I've successfully completed 6 projects while developing at Softaims.

I approach every technical challenge with a mindset geared toward engineering excellence and robust solution architecture. I thrive on translating complex business requirements into elegant, efficient, and maintainable outputs. My expertise lies in diagnosing and optimizing system performance, ensuring that the deliverables are fast, reliable, and future-proof.

The core of my work involves adopting best practices and a disciplined methodology, focusing on meticulous planning and thorough verification. I believe that sustainable solution development requires discipline and a deep commitment to quality from inception to deployment. At Softaims, I leverage these skills daily to build resilient systems that stand the test of time.

I am dedicated to making a tangible difference in client success. I prioritize clear communication and transparency throughout the development lifecycle to ensure every deliverable exceeds expectations.

Main technologies

  • React, AWS and Healthcare Platforms

    5 years

  • React

    1 Year

  • Docker

    3 Years

  • JavaScript

    3 Years

Additional skills

Direct hire

Potentially possible

Previous Company

Infinitt Healthcare

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Experience Highlights

Scalable DICOM Routing & PACS Modernization Platform

Designed and developed a fault-tolerant medical imaging platform handling 100GB+ of DICOM data daily. Implemented asynchronous PACS routing with Redis streams, full C-MOVE/C-STORE support, HAProxy load balancing, and PostgreSQL for reliable metadata storage. Added monitoring stack (Prometheus, Grafana, Loki) and Dockerized microservices for seamless deployment. Delivered production-ready system tested across multiple hospitals with concurrent PACS sources

Cloud PACS Deployment with Orthanc & OHIF

Designed and deployed a cloud PACS solution for medical imaging on AWS EC2 + S3 with Orthanc as the DICOM server and S3 backend for long-term archiving. Implemented anonymization workflows and IAM-based access control to meet healthcare compliance. Deployed OHIF viewer on EC2 with reverse proxy and HTTPS, enabling secure web access to imaging studies. Delivered a scalable, fault-tolerant PACS system with monitoring via Prometheus & Grafana, suitable for hospitals, research centers, and medtech startups.

Distributed DICOM Microservices Platform

Designed a microservices-based platform for distributed DICOM file routing, processing, and storage in healthcare environments. Each service handles ingestion, metadata extraction, cloud backup (S3/MinIO), and monitoring independently, enabling seamless scaling and high availability. The system leverages Docker Compose and HAProxy for orchestration and load balancing, with a React admin dashboard for real-time operations. The modular architecture accelerates integration of new analytics and automation features, making the platform future-proof for AI/ML and large-scale hospital deployments.

ETL Platform for Healthcare Stats

Built a real-time ETL pipeline using Kafka and Flink to deliver instant analytics for hospital operations. Achievements: Reduced data latency from 5s+ to sub-second Designed resilient architecture with Jenkins CI/CD Created backend service for medical/statistical reports with 80%+ test coverage Helped modernize React frontend and mentored team on Zustand + best practices

Medical Image AI Platform

Led full-stack development of a medical AI platform used by hospitals for diagnostic imaging. Migrated legacy desktop app to a scalable web-based architecture, enabling: - GPU-partitioned AI model management - Real-time monitoring dashboards with Grafana - 40% faster model deployment - 35% reduction in system downtime.

Education

  • Sungkyunkwan University

    Master of Science (MS) in

    2020-01-01-2022-01-01

Languages

  • English
  • Korean
  • Russian

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