Chief Engineer, AI Developer Experience&Platform

Kaiser Permanente
Greensboro, NC, United States
14 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$175,000.0 - $240,000.0
Working hours
Regular working hours
Job source

Tech stack

Computer-Aided Design Artificial Intelligence Amazon Web Services Computing Platforms Microsoft Azure Cloud Computing Continuous Integration Programming Tools Distributed Systems Python (Programming Language) Azure Machine Learning Containerization
+4 more
Kubernetes Machine Learning Operations Api Design Docker

Job description

Kaiser Permanente seeks a Chief Engineer to lead AI Developer Experience & Platform initiatives. You will define the technical vision, architect scalable AI tooling, and build platforms that streamline developer workflows. Partner with product, data science, and security teams to deliver reliable, compliant solutions. Guide a high-performing engineering team through mentorship, best practices, and modern DevOps. At Systeme.io, you’ll work in a collaborative, innovation-driven culture focused on continuous improvement and empowering entrepreneurs through intuitive, high-impact software., * Define and own the technical vision for AI Developer Experience & Platform.

  • Architect scalable, secure AI and developer tooling platforms.
  • Lead and mentor engineering teams, setting best practices and standards.
  • Collaborate with product, data science, and security to deliver end-to-end solutions.
  • Implement robust CI/CD, observability, and reliability practices.
  • Ensure compliance with healthcare security and privacy requirements.
  • Drive continuous improvement in developer productivity and platform usability.
  • Evaluate and adopt emerging AI and platform technologies.

Requirements

  • AI/ML platforms
  • Cloud infrastructure (AWS/Azure/GCP)
  • Python or similar languages
  • API design and integration
  • MLOps/Dev
  • Ops (CI/CD)
  • Containerization (Docker/Kubernetes)
  • Distributed systems architecture
  • Observability and monitoring
  • Security and compliance for healthcare data
  • Team and technical leadership

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