Founding AI Engineer for Clinical Workflows

Kabilah

New York (NY)

Vor Ort

USD 150.000 - 230.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Benefits dieser Stelle

Equity (early-stage)
Health insurance
Flexible PTO

Zusammenfassung

Kabilah is hiring a Founding Engineer (AI) in New York to design production AI systems for safety-critical healthcare workflows. You will build the infrastructure, evaluation frameworks, and feedback loops that continuously improve the platform as it learns from clinical practice.

You will own integrations with EHRs and healthcare data sources, optimize latency and observability, and partner with hospital executives and bedside clinicians to rapidly iterate on product capabilities.

Qualifikationen

  • 3+ years of experience building production software.
  • Experience with LLM apps, agentic systems, or AI infrastructure.
  • Experience with cloud infrastructure (AWS, Azure, or GCP).
  • Willingness to travel to customer sites and offsites.

Aufgaben

  • Build the AI infrastructure powering clinical workflows.
  • Design evaluation systems measuring accuracy, reliability, and usefulness.
  • Own integrations with EHRs and clinical data sources.
  • Improve latency, observability, and safety across the AI platform.
  • Collaborate with hospital executives and frontline clinicians to iterate on the product.

Kenntnisse

Production software
LLM AI systems
Cloud platforms
Communication skills

Tools

Cloud platforms (AWS/Azure/GCP)

Jobbeschreibung

Kabilah is hiring a Founding Engineer (AI) in New York to design production AI systems for safety-critical healthcare workflows. You will build the infrastructure, evaluation frameworks, and feedback loops that continuously improve the platform as it learns from clinical practice.

You will own integrations with EHRs and healthcare data sources, optimize latency and observability, and partner with hospital executives and bedside clinicians to rapidly iterate on product capabilities.

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