Infrastructure Operations Engineer in United States at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Infrastructure Operations Engineer in United States.

This is an exciting opportunity for a highly technical infrastructure professional to help operate and scale next-generation AI infrastructure platforms powering advanced machine learning and large-scale compute workloads. In this role, you will work hands-on with GPU environments, Linux systems, cloud infrastructure, and automation frameworks to ensure reliability, performance, and operational efficiency. You’ll collaborate across engineering, networking, and platform teams to solve complex infrastructure challenges and improve system scalability through automation and observability. The position offers exposure to cutting-edge AI technologies, large-scale distributed systems, and modern infrastructure operations in a fast-paced and innovation-driven environment. Ideal candidates are proactive problem-solvers who thrive in highly technical settings and enjoy building resilient systems that support mission-critical AI applications.

• Design, implement, and maintain scalable infrastructure solutions that support large-scale AI and GPU computing environments.
• Manage and optimize Linux-based systems, cloud infrastructure, Kubernetes clusters, and bare-metal environments to ensure platform reliability and operational efficiency.
• Collaborate with infrastructure engineering, networking, software platform, and customer-facing teams to troubleshoot issues and improve service delivery.
• Develop and maintain automation workflows using tools such as Terraform, Ansible, and scripting languages to reduce manual operational overhead.
• Support infrastructure provisioning, monitoring, incident response, and break/fix operations across distributed systems and customer deployments.
• Participate in an on-call rotation, handling critical operational incidents and ensuring high availability of infrastructure services.
• Improve observability and operational tooling through monitoring systems, logging platforms, and infrastructure performance analysis.
• Contribute to the deployment of new platforms, features, and operational patterns that enhance scalability, resilience, and customer experience.

• 8+ years of experience managing Linux server or hosting environments, preferably including Ubuntu systems.
• 5+ years of hands-on experience with AWS cloud infrastructure and services.
• Strong expertise in Kubernetes, containerization technologies, and GitOps workflows.
• Experience with infrastructure-as-code and automation tools such as Terraform and Ansible.
• Knowledge of network-attached storage technologies including NFS, Ceph, or similar systems.
• Experience with monitoring and observability platforms such as Prometheus and ELK stack.
• Proficiency in scripting or software development for automation using Python, Go, Bash, or similar languages.
• Strong networking fundamentals, with additional experience in data center networking, Infiniband, or high-speed Ethernet considered a plus.
• Familiarity with GPU infrastructure, bare-metal provisioning, and hardware troubleshooting is highly desirable.
• Excellent communication, analytical thinking, and problem-solving skills with the ability to navigate ambiguity and technical complexity.

• Competitive compensation package with bonus opportunities and equity participation.
• Annual base salary range of approximately $160,000 – $200,000 USD depending on experience and location.
• Comprehensive medical, dental, and vision coverage.
• Retirement and financial wellness support programs.
• Generous paid time off and company holidays.
• Paid parental leave and family support benefits.
• Flexible remote or hybrid work environment within the United States.
• Professional development resources and career growth opportunities.
• Wellness and home office stipends to support remote productivity and employee well-being.
• Inclusive and collaborative company culture focused on innovation and continuous learning.