Machinify, a leading healthcare intelligence company that leverages AI to maximize financial outcomes for health plans, is seeking a DevOps Engineer. This critical role is focused on automating and maintaining the company’s AI/ML cloud technologies, with a primary focus on the migration of VM technologies into Kubernetes environments.

This is a full-time, fully remote position in the United States. The salary range is $150,000.00 – $180,000.00 per year.

Role Summary and Kubernetes Migration Mandate

The DevOps Engineer will provide technical leadership across automation, programming, and system operations. The mandate is to ensure the Machinify Cloud operates at big data scale, high uptime, and with operational excellence. You will be directly responsible and accountable for the design, engineering, and integration within production environments, focusing on future-proof implementations while solving current scaling challenges.

Key Responsibilities:

• Kubernetes Migration: Facilitate the movement of VM technologies into Kubernetes through migration or replacement for all applicable solutions.
• Automation: Automate everything to ensure zero manual intervention, routinely redeploying systems from the ground up to validate automation integrity.
• Architecture: Architect solutions to achieve a high level of performance, reliability, scalability, and security for the distributed compute environment.
• AI/ML Technologies: Create, maintain, and troubleshoot distributed compute AI/ML technologies running in the Cloud.
• Configuration Management: Plan, design, and execute the successful build and deployment of code updates and implement the configuration management of all underlying technologies.
• Compliance & Security: Work in/create compliant environments such as Hi-Trust/SOC2 and apply good Operations security practices.

Required Experience and Technical Qualifications

The ideal candidate is an experienced, logical problem-solver with a strong background in production cloud environments, deep Kubernetes skills, and exposure to distributed AI/ML frameworks.

• Experience (Required):
  • 5+ years of production support, preferably in a Cloud Environment (AWS, Azure, or GCP).
  • Experience in the migration of VM Technologies into a Kubernetes Environment.
• Core Technical Knowledge:
  • Containerization with Kubernetes
  • Scripting (Python, shell, etc.)
  • Crossplane / Terraform (Infrastructure as Code)
  • Linux (CentOS/RHEL)
  • Spark / Machine Learning running in the Cloud
  • Frameworks for distributed machine-learning / AI, such as Azure OpenAI, AWS Bedrock, TensorFlow, and MxNet.
  • Continuous Integration/Continuous Deployment frameworks.
• Compliance & Security:
  • Good understanding of Operations security practices.
  • Working in / creating compliant environments such as Hi-Trust / SOC2, etc.
• Education & Skills: Degree in Computer Science or equivalent work experience. Must be extremely logical with the ability to solve problems in creative and efficient ways, and demonstrate critical thinking.