Abstract : Power-system modernization increasingly depends on artificial intelligence (AI), digital twins, and continuous operational visibility to maintain resilience, reliability, and situational awareness across evolving grid environments. This paper presents DEVOPS-GRID, a DevOps-driven operating model for intelligent power systems that integrates infrastructure automation, observability, deployment governance, digital-twin feedback loops, and automated remediation for grid-facing software and analytics services. Unlike conventional utility operations that separate release workflows from system-state intelligence, the proposed model aligns cloud-native delivery practices with power-system reliability engineering. The paper defines a layered architecture spanning delivery governance, infrastructure automation, observability, digital twin synchronization, and self-healing orchestration. A simulated distribution network scenario demonstrates measurable improvements in mean time to detect (MTTD), mean time to remediate (MTTR), and configuration drift rates relative to conventional operating baselines. The model further addresses compliance alignment with IEC 61850, IEC 61970, NERC CIP-010, and IEEE C37.118 standards. Results suggest that integrating DevOps discipline with power-system engineering can materially improve operational consistency, incident response velocity, and controlled change management in AI-enabled grid environments.