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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in implementing AIOps solutions and optimizing observability platforms, with a strong focus on automation workflows and AI/ML model deployment for IT operations. Proficient in cloud infrastructure operations and observability engineering, ensuring compliance with security and governance standards.
Highest-signal resume keywords
AIOps ImplementationObservability Tools (ELK, Prometheus, Grafana)Automation Frameworks (Ansible, ServiceNow)Scripting Languages (Python, PowerShell, Bash)Cloud Platforms (Azure, AWS, GCP)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
AIOps ImplementationObservability EngineeringAutomation EngineeringScripting (Python, PowerShell, Bash)Cloud Infrastructure OperationsAI/ML Model DeploymentEvent ManagementCorrelation EnginesTopology MappingCMDB Integrations
Tools & Technologies
ELK/ElasticPrometheusGrafanaDynatraceAppDynamicsDatadogNew RelicSplunkAnsibleServiceNow
Industry Keywords
Cloud OperationsObservabilityIncident DetectionAutomated RemediationOperational SignalsSecurity ComplianceGovernanceIAMData Handling GuidelinesOperationalization
Tech Stack
Tools & technologiesAnsibleAWSAzureCloudGoogle Cloud PlatformGrafanaPrometheusPythonServiceNowSplunk
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- Competitive salary