DevOps Support Engineer
About
NeuroHire is a Texas-based SaaS company building AI-powered hiring solutions. Our platform depends on reliable infrastructure, smooth deployments, and real-time system performance.
We’re looking for a DevOps Support Engineer who can help maintain system stability, support deployments, and quickly resolve issues to ensure a seamless user experience.
Role Overview
As a DevOps Support Engineer, you will work closely with engineering and cloud teams to support production systems, monitor infrastructure, and troubleshoot issues.
This role is ideal for someone who enjoys working on live systems, solving real-time problems, and improving system reliability in a fast-paced environment.
What You’ll Work On
- Monitor application and infrastructure performance across environments
- Troubleshoot and resolve production issues, incidents, and outages
- Support CI/CD pipelines and deployment processes
- Work with cloud environments such as AWS, Azure, or GCP
- Analyze logs, alerts, and system metrics to identify issues
- Assist in maintaining system uptime and availability
- Collaborate with development teams to resolve bugs and performance issues
- Automate routine operational tasks where possible
- Document processes, fixes, and troubleshooting steps
What We’re Looking For
- Bachelor’s degree in Computer Science, IT, or related field
- 1–4 years of experience in DevOps, support, or system administration roles
- Experience with cloud platforms (AWS / Azure / GCP)
- Familiarity with CI/CD tools (GitHub Actions, Jenkins, GitLab CI, etc.)
- Basic knowledge of Linux/Unix systems
- Experience with monitoring and logging tools
- Understanding of APIs, web applications, and system architecture
- Strong problem-solving and troubleshooting skills
Nice to Have
- Experience with Docker, Kubernetes, or container-based systems
- Familiarity with Infrastructure as Code (Terraform, CloudFormation)
- Exposure to scripting (Bash, Python)
- Experience in SaaS or production environments
- Knowledge of cloud security best practices