Site Reliability Engineer

Cisco · Bengaluru · 5+ yrs experience · Posted 2026-06-16

Tech stack: Ansible, C, C++, Docker, GitHub Actions, Go, Jenkins, Kubernetes, Linux, Python, Terraform

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About the role

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.
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
Qualifications:
- You are an experienced Site Reliability Engineer or AI infrastructure engineer with a strong technical background in designing, building, and supporting complex AI and HPC systems. You work well with others, communicate clearly, and enjoy solving challenging technical problems. You are eager to learn new technologies and approaches, and are passionate about building and operating high-performance, reliable AI infrastructure at scale.
- Minimum Requirements
- Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent years of experience.
- 5+ years of experience administering and supporting Linux-based operating systems in enterprise environments.
- Strong hands-on experience in deploying and managing NVIDIA DGX or equivalent HPC clusters (e.g., Cray, HPE, IBM), including working with AI factory architectures.
- Experience working with business clients or technical teams to gather requirements and deliver AI platform solutions.
- Proficient in Python, Go, or C/C++, with practical experience in Git and CI/CD systems (e.g., GitHub Actions, GitLab, Jenkins).
- Experience with Kubernetes clusters (RedHat OpenShift preferred), Docker, Terraform, Ansible, and GitOps methodologies.
- Strong troubleshooting, incident management, and process automation skills.
- Master’s degree in a relevant field.
- Certifications in NVIDIA, Cisco, Linux, Networking, Cloud, or related technologies.
- Experience contributing to the design and operation of AI factories or large-scale HPC systems.
- Expertise with Kubernetes, Hybrid Cloud, Virtualization, and container technologies.
- Exposure to Agile and DevOps operating models and project tracking tools (e.g., Jira, Rally).
- Demonstrated ability to collaborate and communicate advanced technical concepts in a team environment.

Qualifications

- You are an experienced Site Reliability Engineer or AI infrastructure engineer with a strong technical background in designing, building, and supporting complex AI and HPC systems.
- You work well with others, communicate clearly, and enjoy solving challenging technical problems.
- You are eager to learn new technologies and approaches, and are passionate about building and operating high-performance, reliable AI infrastructure at scale.
- Minimum Requirements Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent years of experience.
- 5+ years of experience administering and supporting Linux-based operating systems in enterprise environments.
- Strong hands-on experience in deploying and managing NVIDIA DGX or equivalent HPC clusters (e.g., Cray, HPE, IBM), including working with AI factory architectures.
- Experience working with business clients or technical teams to gather requirements and deliver AI platform solutions.
- Proficient in Python, Go, or C/C++, with practical experience in Git and CI/CD systems (e.g., GitHub Actions, GitLab, Jenkins).
- Experience with Kubernetes clusters (RedHat OpenShift preferred), Docker, Terraform, Ansible, and GitOps methodologies.
- Strong troubleshooting, incident management, and process automation skills.
- Master’s degree in a relevant field.
- Certifications in NVIDIA, Cisco, Linux, Networking, Cloud, or related technologies.
- Experience contributing to the design and operation of AI factories or large-scale HPC systems.
- Expertise with Kubernetes, Hybrid Cloud, Virtualization, and container technologies.
- Exposure to Agile and DevOps operating models and project tracking tools (e.g., Jira, Rally).
- Demonstrated ability to collaborate and communicate advanced technical concepts in a team environment.

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

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