Software Engineer (Cloud Infrastructure)

Location: Hybrid role based in San Jose, California, or Morrisville, North Carolina, United States; some in-office and in-person expectations apply.

Company

hirify.global develops intelligent data infrastructure, unified storage, integrated data services, and cloud solutions supporting traditional workloads and enterprise AI.

What you will do

• Develop and maintain software, scripts, command-line tools, APIs, and automation for cloud infrastructure deployment and operations.
• Build operational tooling with Python, Golang, PowerShell, and Kubernetes to reduce manual production procedures.
• Perform functional, integration, regression, and reliability testing; document results and resolve defects.
• Troubleshoot software, infrastructure, networking, and configuration issues using logs, metrics, traces, and other diagnostics.
• Participate in incident response, on-call operations, root-cause investigations, and corrective actions.
• Collaborate with software, production engineering, networking, security, hardware, and program-management partners on reliable and secure solutions.

Requirements

• 4+ years of experience in software development, cloud engineering, DevOps, infrastructure automation, or site reliability engineering.
• Working knowledge of Python and Golang.
• Experience with automation for Linux or other Unix-like operating systems.
• Familiarity with source control, pull requests, code reviews, automated testing, and CI/CD practices.
• Working knowledge of REST APIs and JSON or YAML, plus familiarity with public-cloud services, preferably Microsoft Azure, Docker, or Kubernetes.
• Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Information Technology, or a related technical field; equivalent practical experience is accepted.

Culture & Benefits

• Hybrid working environment designed to support collaboration and connection.
• Opportunity to work on cloud services, storage, infrastructure automation, enterprise AI, and multicloud technologies.
• Emphasis on initiative, impact, ownership, inclusion, flexibility, and work-life balance.
• Some hiring-process stages may use AI tools to support application evaluation and candidate selection.