| Job Description: |
Must Have Technical/Functional Skills
• Strong expertise in AI Ops / MLOps / LLM Ops practices
• End-to-end model lifecycle management
• Advanced model monitoring, observability, and alerting frameworks
• Drift detection, performance tracking, and automated retraining
• CI/CD and DevSecOps for AI/ML systems
• Scalable deployment architectures for AI/ML and LLM
• AI governance, risk, security, and compliance frameworks [
• AI platform engineering and operational tooling experience
• Performance optimization (latency, cost, scalability) for AI workloads
• Strong experience in automation of AI operations workflows
• Data pipeline integration and ML infrastructure management
• Cross-functional collaboration with engineering, data, and platform teams
Roles & Responsibilities
• Define and implement AI Ops / MLOps / LLM Ops strategy for enterprise AI platforms
• Manage end-to-end AI operations lifecycle (deployment, monitoring, scaling, optimization)
• Establish model monitoring, observability, and alerting frameworks for production AI systems
• Implement model lifecycle management (versioning, deployment, retraining, rollback, drift detection)
• Define and track AI Ops KPIs (performance, reliability, incident reduction, automation efficiency)
• Ensure high availability, scalability, and performance of AI systems in production
• Drive adoption of CI/CD and DevSecOps practices for AI/ML systems
• Implement governance, risk, security, and compliance controls for AI systems
• Collaborate with AI engineering, data, and platform teams for seamless operation
• Manage incident response, root-cause analysis, and continuous improvement for AI system
• Optimize cost, latency, and resource utilization of AI workloads
• Drive automation of AI operations processes and workflows
Role Descriptions: AI Ops Leader
Skills: AI for Leadership
Experience Required: 10 & Above
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