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Prolaio is seeking a Site Reliability Engineer to ensure the cardiovascular data platform reliably captures, transports, and delivers continuous biosensor data for researchers. You will build monitoring, define SLOs, manage incident response, and automate to keep critical data flows healthy.
You will investigate incidents across the participant-to-platform stack, determine root causes across hardware, firmware, apps, and connectivity, and implement durable improvements to reduce toil and improve
Prolaio believes that continuous learning and collaboration can make a significant difference in how heart care is administered. We are creating smarter ways to address heart disease and heart risks by uniting patients, care teams, and researchers on a secure, technology-enabled platform that drives clinical innovation and offers a path towards better patient outcomes.
This is precision cardiology, and we know it's within reach.
What Will You Do?
The Overview
The Site Reliability Engineer will ensure that Prolaio's cardiovascular data platform reliably captures, transports, and delivers continuous biosensor data from participants to the clinical researchers and trial sponsors who depend on it. In this role, you will build and operate the monitoring, service level objectives, incident response, and automation needed to keep critical data flows healthy, identify failures before they impact studies, and ensure that device downtime never goes unnoticed simply because a shipment record says a device was delivered.
This role is ideal for a self-starter who thrives at the intersection of software reliability, connected devices, and clinical data. You will investigate incidents across the full participant-to-platform stack, combining service telemetry with device data and participant reports to determine whether an issue originated with the hardware, phone, firmware, mobile application, connectivity, or the platform itself. You will turn those investigations into durable improvements, automating manual checks, strengthening observability, reducing operational toil, and building the reliability practices that keep Prolaio's clinical data complete and trustworthy at scale.
The Specifics