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DeepHealth

AI-driven medical imaging and informatics platform

Senior Site Reliability Engineer

Site Reliability EngineeringUpdated on Nov 13
Full-timeNo salary listedIn-person

About the Job

Responsibilities

  • Own the reliability, availability, and performance of cloud components deployed at client sites and of the DeepHealth solution.
  • Define and monitor service level objectives (SLOs), error budgets, and key reliability metrics.
  • Develop and implement automation tools and processes to eliminate toil and streamline deployment, monitoring, and incident response operations.
  • Design and maintain observability tooling for monitoring, logging, alerting, and tracing, and resolve issues before they impact clients.
  • Contribute to writing technical specifications and documentation, ensuring compliance with regulatory requirements and industry best practices.
  • Lead incident response, conduct blameless post-mortems, and drive implementation of corrective and preventive actions.
  • Perform capacity planning and performance tuning to anticipate growth and ensure optimal resource utilization.
  • Support deployment of software solutions at customer sites, ensuring smooth implementation and optimal performance.
  • Provide ongoing support and maintenance for deployed solutions and the operational team, addressing issues or challenges to maintain high customer satisfaction.
  • Mentor and onboard engineers, providing technical leadership in SRE and platform engineering best practices.
  • Implement and maintain secure infrastructure configurations per approved baselines.
  • Ensure CI/CD pipeline security, including integrity verification and access controls.
  • Perform day-to-day technical security controls, including system hardening and log monitoring.
  • Document all infrastructure changes and maintain audit trails.

About the Company

DeepHealth

AI-driven medical imaging and informatics platform

DeepHealth provides AI-powered medical imaging and health informatics solutions that help radiologists analyze X-rays, CTs, and MRIs by automating parts of image interpretation, highlighting areas of concern, and delivering quantitative insights. It works by integrating AI into radiology workflows via cloud-based software, enabling automated image analysis, scoring, and reporting within enterprise imaging systems. The company differentiates itself through its integration with RadNet and strategic acquisitions of iCAD and CIMAR UK, expanding breast imaging capabilities, interoperability, and the scale of its deployments. Its goal is to accelerate the adoption of AI in real-world healthcare, improve diagnostic accuracy and consistency, and streamline imaging workflows across hospitals and health systems.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Cambridge, MA
Founded
2017

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