Site Reliability Engineer

Your Role as a Cisco IT AI Infrastructure Site Reliability Engineer

Are you passionate about shaping the future of artificial intelligence and ensuring its robust, enterprise-scale operation? Join Cisco IT as an AI Infrastructure Site Reliability Engineer, where you will play a key technical role in building, developing, optimizing, and supporting complex AI architectures built on cutting-edge NVIDIA DGX and Cisco-UCS based AI platforms. You will help drive innovation and reliability across our foundational AI infrastructure, supporting Cisco’s most critical business and technology initiatives.

In this role, you will work closely with peers, technical teams, and internal business clients to ensure the reliability, scalability, and efficiency of our AI solutions. You will leverage Site Reliability Engineering (SRE) best practices and automation to continually improve operational excellence and service quality for Cisco’s AI platforms.

Responsibilities include:

- Design and Implementation: Contribute to the design, deployment, and optimization of AI infrastructure, including high-performance compute (HPC) systems, data center power & cooling, network topologies, and the AI factory software stack.

- System Administration: Configure, maintain, and troubleshoot AI platforms, including NVIDIA DGX and Cisco Unified Compute Systems with NVIDIA/AMD GPUs.

- Collaboration: Work with internal business clients and technical teams to understand technical requirements and translate them into robust, scalable AI platform solutions.

- SRE Practices: Apply SRE principles to automate operational processes, reduce toil, and help maintain service level objectives (SLOs) for AI platforms.

- Automation: Develop and maintain CI/CD pipelines using Python, Ansible, Terraform, Go, and GitHub Actions to streamline operational capabilities and continuous improvements.

- Capacity and Performance: Participate in capacity planning, performance analysis, instrumentation, and support non-functional requirements to ensure efficient and reliable AI infrastructure.

- Incident Response: Participate in incident management, troubleshooting, hardware break/fix support, and root cause analysis to resolve issues and ensure high availability.

- Continuous Improvement: Contribute to ongoing process automation, optimization, and documentation to enhance service quality and operational efficiency.