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Medium due to Bangalore location and generalist DevOps requirements, tempered by niche AI-infrastructure skills.
High because role demands deep AI-infrastructure, Kubernetes, HPC, and storage expertise limiting transferability.
High because 8+ years plus mandatory Kubernetes, Linux, and IaC automation requirements.
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Develop, integrate, and validate software solutions for enterprise AI infrastructure across a broad technology stack including Linux, Kubernetes, HPC, networking, storage, GPUs, AI frameworks, and cloud-native infrastructure.
Design and implement automation tools (e.g., Ansible, Python, GitLab CI/CD, Helm) to improve deployment, validation, and operational workflows, enhancing reliability and repeatability.
Troubleshoot complex systems issues and collaborate with cross-functional teams to identify root causes and deliver technical solutions while contributing to continuous platform improvements.
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Minimum 8 years of experience managing and scaling Linux-based production environments.
Deep expertise in Kubernetes architecture, deployment, and operations; strong experience with infrastructure automation and Infrastructure as Code (Ansible preferred).
Advanced scripting skills in Python or Bash; proficiency with Git, CI/CD pipelines, and cloud-native development practices.
Experienced systems engineer with significant experience in enterprise AI infrastructure and large-scale Linux/Kubernetes environments.
Operates effectively across multidisciplinary teams, providing technical leadership and mentoring while influencing technical strategies.
Skilled in automation and modern DevOps practices, with a track record of solving complex distributed system problems and integrating emerging AI infrastructure technologies.