AIOPs Platform Engineer-Senior

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Job Title: AIOps Strategy & Implementation Engineer – Senior

Job Summary:

We are seeking a Senior AIOps Strategy & Implementation Engineer with up to 8 years of experience in observability platforms, automation workflows, cloud/infrastructure operations, and AI-driven operational analytics. The ideal candidate will have hands-on experience implementing AIOps capabilities, integrating monitoring/telemetry systems, building automation pipelines, and supporting AI/ML model deployment focused on IT operations—not traditional ML development.

Key Responsibilities:

• Implement and integrate AIOps solutions across cloud and on-prem environments to enhance incident detection, correlation, and automated remediation.
• Configure, manage, and optimize observability platforms (logs, metrics, traces) including ingestion pipelines, dashboards, alerting rules, and topology views.
• Build automation workflows for operational tasks such as event triage, remediation actions, resource optimization, and predictive maintenance.
• Collaborate with platform, cloud, and operations teams to onboard new services, data sources, and operational signals into the AIOps ecosystem.
• Support deployment, integration, and operationalization of AI/ML models used for anomaly detection, event correlation, forecasting, and noise reduction (not model training).
• Develop and implement playbooks, runbooks, and automated actions in line with SRE, DevOps, and cloud operations practices.
• Troubleshoot issues related to observability ingestion, integration connectors, pipeline performance, and automation workflows.
• Participate in architectural discussions, tool evaluations, and AIOps capability uplift initiatives.
• Ensure compliance with security, governance, IAM, and data handling guidelines in the AIOps and observability ecosystem.
• Document configurations, workflows, integrations, and operational guidelines for AIOps platform usage.

Qualifications:

• Up to 8 years of experience in cloud/infrastructure operations, SRE, observability engineering, or automation engineering.
• Strong hands-on experience with observability tools (e.g., ELK/Elastic, Prometheus, Grafana, Dynatrace, AppDynamics, Datadog, New Relic, Splunk, or equivalent).
• Experience building workflows using automation frameworks or orchestration tools (e.g., Ansible, ServiceNow, Rundeck, Azure Automation, Lambda/Functions).
• Familiarity with AI/ML model deployment concepts for IT operations (consumption of models, not development).
• Understanding of event management, correlation engines, topology mapping, and CMDB integrations.
• Proficiency with scripting languages (Python, PowerShell, Bash) for automations and integrations.
• Knowledge of cloud platforms (Azure/AWS/GCP), their monitoring services, and operational data flows.
• Bachelor’s degree in Information Technology, Computer Science, or related discipline.

Preferred Skills:

• Experience with SRE practices, auto-remediation frameworks, and service health modeling.
• Understanding of log pipelines, telemetry routing, data normalization, and enrichment.
• Exposure to ITSM platforms and integrations (ServiceNow preferred).
• Strong analytical skills for troubleshooting observability and automation issues.
• Ability to work across multiple teams, communicate technical concepts clearly, and support platform adoption.

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