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OpenShift & Python Developer

Job in Chandler, Maricopa County, Arizona, 85249, USA
Listing for: Veriipro
Full Time position
Listed on 2026-06-18
Job specializations:
  • IT/Tech
    Cloud Computing: Infrastructure & Operations, AI Engineer (Applied/Software), SRE/Site Reliability
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

We are seeking an experienced Open Shift and Python Developer to design, deploy, and maintain containerized infrastructure for cutting‑edge AI/ML workloads. The ideal candidate will have deep expertise in Python development, container orchestration, and Red Hat Open Shift, and will lead initiatives to build scalable, secure, and automated platform solutions.

Required Technical Skills
  • Core Python programming and scripting
  • Red Hat Open Shift
  • Kubernetes and container platforms (Docker, CRI‑O, etc.)
  • GPU infrastructure enablement for AI/ML workloads
  • Infrastructure automation and platform tooling
Roles and Responsibilities
  • Lead the end‑to‑end setup, deployment, and management of Open Shift‑based container infrastructure for GenAI workloads.
  • Design, implement, and optimize Kubernetes/Open Shift clusters for scalability, performance, and security.
  • Enable and manage GPU infrastructure within Open Shift for AI/ML and GenAI applications.
  • Develop automation, tooling, and workflows using Python to streamline platform operations.
  • Define platform standards, operational best practices, and implementation roadmaps.
  • Collaborate with architecture, Dev Ops, security, and application teams to ensure production‑ready delivery.
  • Provide technical leadership and mentor team members across infrastructure initiatives.
Preferred Qualifications
  • Experience with CI/CD pipelines and Git Ops practices
  • Familiarity with cloud platforms (AWS, Azure, GCP)
  • Strong understanding of networking, storage, and security in containerized environments
  • Proven experience supporting AI/ML workloads in production
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