Lead DevOps Engineer (AI & GPU)

📋 Description

• Lead the design, implementation, and operation of CI/CD and continuous verification (CV) pipelines
• Implement and manage GitOps-based deployment workflows using tools such as Argo CD, Helm, GitHub
• Operate and optimize production-scale AI inference and model-serving infrastructure using
• Manage AI asset governance and discovery, including artifact and container registries, model
• Integrate tools such as Harbor, Artifactory, Nexus, MLflow, Hugging Face, NVIDIA GPU Cloud (NGC)
• Design and maintain a comprehensive observability platform encompassing metrics, logs, traces

🎯 Requirements

• Bachelor's or Master's degree in Computer Science or a related technical discipline.
• At least 8 years of professional experience in DevOps, MLOps, platform engineering, observability
• Strong expertise in CI/CD pipeline design, continuous verification, GitOps practices, automated
• Practical experience with GitOps and automation tools such as Argo CD, Helm, GitHub Actions, GitLab
• Demonstrated experience operating production-scale AI inference and model-serving systems
• Strong understanding of GPU-enabled workloads, inference performance optimization, resource

🎁 Benefits

• Remote work flexibility: Opportunity to work remotely from India, with Bangalore identified as the
• Full-time employment: Join a technical team focused on building and operating advanced AI
• Technical leadership opportunities: Influence AI platform architecture, deployment standards
• Advanced technology exposure: Work with modern AI inference frameworks, GPU computing, cloud-native
• Professional development: Expand your expertise in AI infrastructure, MLOps, FinOps, platform
• Cross-functional collaboration: Partner with engineering, platform, security, and data teams to