Elastic AIOps Engineer

Key skills

• Machine Learning
• Data Modeling
• Devops

Job description

Hands-on experience with the Elastic Stack in production (Elasticsearch, Logstash, Kibana, Beats/Elastic Agent, APM), including ingestion pipelines, ILM, and performance tuning

Responsibilities:

Hands-on experience with the Elastic Stack in production (Elasticsearch, Logstash, Kibana, Beats/Elastic Agent, APM), including ingestion pipelines, ILM, and performance tuning

-- Strong understanding of observability concepts: logs, metrics, traces, SLOs/SLIs, and alerting, with experience building Kibana dashboards, service maps, and alerts

-- Working knowledge of OpenTelemetry and Any Enterprise APM for standardized instrumentation and ECS-based data modeling

-- Experience with Elastic Machine Learning for anomaly detection, forecasting, and log categorization

-- Knowledge of AIOps practices such as event correlation, alert noise reduction, root cause analysis, and automated remediation, with integrations to ITSM tools like ServiceNow or PagerDuty

-- Good to have: exposure to AI for observability, including LLMs, RAG, vector/semantic search, and Elastic AI Assistant for Observability

Preferred Skills:

Technology->DevOps and Continuous Testing->Continuous delivery - Continuous deployment and release->Elastic Logstash and Kibana (ELK)

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