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AI Infrastructure Engineer

AI Infrastructure Engineer

Cisco

5 - 9 years

0 Lacs

karnataka

Posted:2 weeks ago| Platform: Shine logo

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Skills Required

rust python linux kubernetes cc golang ebpf crds

Work Mode

On-site

Job Type

Full Time

Job Description

You will be part of an innovation team at Cisco with a mission to revolutionize how enterprises leverage AI. Operating with the agility of a startup and the focus of an incubator, you will collaborate with a team of AI and infrastructure experts driven by bold ideas. Your shared goal will be to rethink systems from the ground up and deliver innovative solutions that redefine what is achievable, faster, leaner, and smarter. You will thrive in a fast-paced, experimentation-rich environment that welcomes new technologies and work alongside seasoned engineers, architects, and thinkers to craft iconic products that can reshape industries and introduce new operational models. - Design and develop node-level infrastructure components to support high-performance AI workloads. - Benchmark, analyze, and optimize the performance of AI infrastructure, including CUDA kernels and memory management for GPUs. - Ensure minimal downtime through seamless configuration and upgrade architecture for software components. - Manage the installation and deployment of AI infrastructure on Kubernetes clusters, including the utilization of CRDs and operators. - Develop and deploy efficient telemetry collection systems for nodes and hardware components without impacting workload performance. - Utilize distributed system fundamentals to ensure scalability, resilience, and reliability. - Collaborate across teams and time zones to influence the overall direction of AI infrastructure development and achieve shared objectives. - Proficiency in programming languages such as Rust, C/C++, Golang, Python, or eBPF. - Strong understanding of Linux operating systems, including user space and kernel-level components. - Experience with Linux user space development, including packaging, logging, telemetry, and lifecycle management of processes. - Strong understanding of Kubernetes (K8s) and related technologies, such as custom resource definitions (CRDs). - Strong debugging and problem-solving skills for complex system-level issues. - Bachelor's degree+ and relevant 5+ years of Engineering work experience.,

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AI Infrastructure Engineer