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OpenEvidence

AI-driven clinical decision support for care

Member of Technical Staff - Health Systems

Software EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 3 years of professional engineering experience.
  • Strong engineering ability and product judgment, particularly around risk, reliability, and production changes.
  • Ability to understand complex systems and quickly identify the source of a problem.
  • Strong written and verbal communication skills for sophisticated enterprise audiences and non-technical clinical leaders.

Responsibilities

  • Lead the design, build, and launch of OpenEvidence within health systems, from product ideation through ongoing support.
  • Make product and architectural decisions, often in ambiguous situations.
  • Build enterprise product capabilities and turn recurring needs into scalable tools and processes.
  • Uphold the security, privacy, and reliability standards expected by health system partners.
  • Work across engineering, product, sales, support, legal, and partners to deliver outcomes.
  • Design the future of OpenEvidence within clinical workflows and shape the product built into clinicians' existing work environments.
  • Define, build, and launch solutions when clinicians or partners need something that does not yet exist.
  • Write or review code, prototype clinical workflows, set technical direction for launches, shape the product roadmap based on clinician and partner input, and present plans to health system IT, security, and clinical leaders.

Desired Qualifications

  • At least 5 years of professional engineering experience.
  • Experience with health systems, electronic health record integrations, clinical AI benchmarking, agentic workflows, and enterprise software-as-a-service implementations.

About the Company

OpenEvidence

AI-driven clinical decision support for care

OpenEvidence builds AI-driven clinical decision support tools that help healthcare professionals make better choices at the point of care. It creates AI models and interfaces that integrate with existing platforms (notably through Mayo Clinic Platform Accelerate) and partner ecosystems like Elsevier Health to power products such as ClinicalKey AI. Clinicians use these tools inside their regular clinical workflows, with AI assisting by analyzing medical literature, guidelines, and patient data to suggest evidence-based options.

Company size
51-200
Company stage
Late Stage VC
Total funding
$1B
Headquarters
Miami, FL
Founded
2022

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