EY is seeking an experienced AIOps Manager to architect and implement enterprise-grade AIOps solutions. This role focuses on automating incident detection, root cause analysis, and remediation across cloud and hybrid environments. You will lead the integration of telemetry data into centralized AIOps platforms for unified observability and intelligent event correlation.

This position involves designing and maintaining ML models for anomaly detection and predictive analytics, building real-time data pipelines, and collaborating with DevOps and SRE teams to embed AIOps into CI/CD workflows. The role also requires driving automation of operational tasks, developing insightful dashboards, and implementing strategies to reduce alert noise.

Furthermore, you will ensure compliance with security and governance policies, lead technical evaluations of AIOps tools, and mentor a team of AIOps engineers. The position also entails partnering with business stakeholders to identify opportunities for cost optimization and service reliability improvements. You will contribute to strategic roadmaps and stay abreast of emerging trends in AIOps and AI-driven automation.

Architect and implement enterprise-grade AIOps solutions for automated incident detection, root cause analysis, and remediation. Lead the integration of telemetry data from various tools into centralized AIOps platforms. Design and maintain ML models for anomaly detection, predictive analytics, and operational forecasting. Build and optimize real-time and batch data pipelines using tools like Kafka, Logstash, and Fluentd. Collaborate with DevOps, SRE, and platform engineering teams to embed AIOps into CI/CD workflows and IaC practices. Drive automation of operational tasks and remediation workflows using Python and orchestration tools. Develop dashboards and visualizations using Grafana, Kibana, or Power BI for actionable insights. Implement alert noise reduction strategies using ML-based filtering and suppression techniques. Ensure compliance with security, governance, and audit policies, embedding DevSecOps principles. Lead technical evaluations of AIOps platforms and tools. Manage and mentor a team of AIOps engineers, fostering innovation and operational excellence. Partner with business stakeholders to identify opportunities for cost optimization and service reliability improvements. Contribute to strategic roadmaps, budget planning, and vendor assessments. Stay current with emerging trends in AIOps and AI-driven automation.

A minimum of 9 years of experience in IT operations, DevOps, or SRE, with at least 3 years focused on AIOps or AI/ML-driven automation, is required. Proven experience in technical leadership, team management, and cross-functional collaboration is essential.

Deep expertise in AIOps platforms such as Moogsoft, BigPanda, Splunk ITSI, ServiceNow ITOM, or custom ML-based solutions is necessary. Strong proficiency in Python, coupled with working knowledge of SQL, PowerShell, and Bash, is expected. Hands-on experience with cloud environments like Azure, AWS, or GCP, including their monitoring and automation services, is crucial.

Skilled in CI/CD tools (Azure DevOps, GitHub Actions, Jenkins), Infrastructure as Code (Terraform, Ansible), and Kubernetes is required. Familiarity with observability stacks (ELK, OpenTelemetry, Kafka) and data engineering workflows is also important. Excellent communication, stakeholder management, and problem-solving skills are fundamental for this role.