Lead AIOps Engineer
Core
Build and scale AI-driven operations across the full service management lifecycle to improve reliability, reduce manual effort, and accelerate recovery.
Role type
Lead AIOps Engineer
Builds
Production-grade AIOps capabilities including event correlation, anomaly detection, predictive monitoring, and intelligent workflow automation.
Domain
IT Operations / Service Management / AI Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
Python, ML model training and deployment, operational telemetry (metrics/logs/events/traces), data pipeline engineering, automation/orchestration, technical leadership, system design
Preferred skills
AIOps platforms, ML lifecycle management, Kubernetes, Infrastructure as Code, cloud platforms
Technologies
Python, Kubernetes, Cloud platforms, ML frameworks
Responsibilities
Build and deploy AIOps capabilities to reduce alert fatigue; Develop and productionize ML approaches for anomaly detection and predictive monitoring; Design and implement data pipelines for operational signals; Create automation scripts and workflows for incident response; Engineer AI-native service management workflows; Partner with teams to automate release and change activities; Establish engineering standards for model performance and safe automation; Mentor engineers through technical leadership.
Seniority
Senior, hands-on IC with leadership responsibilities
