Elastic AIOps Engineer

Infosys; Bengaluru; In loco; INR 1.500.000 - 2.500.000; Tempo pieno

Descrizione del lavoro

Infosys is seeking an Elastic AIOps Engineer to join our Bangalore team for immediate joining. You will design and operate production-grade Elastic Stack solutions, focusing on observability, anomaly detection, and automated remediation.

You should be proficient with Elasticsearch, Logstash, Kibana, Beats/Elastic Agent, and APM, and comfortable integrating with ITSM tools. Exposure to OpenTelemetry and AI-enabled observability is a plus, driving reliability and insights across services.

Competenze

• Hands-on experience with Elastic Stack in production.
• Understanding of observability: logs, metrics, traces, SLOs/SLIs, and alerting.
• Experience with OpenTelemetry and instrumentation.
• Experience with Elastic Machine Learning for anomaly detection.
• Knowledge of AIOps practices and ITSM integrations.

Mansioni

• Design and operate Elastic Stack pipelines in production.
• Implement observability with logs, metrics, traces and alerts.
• Integrate AIOps workflows and ITSM tools for automated remediation.
• Experiment with AI-assisted observability features as they relate to Elastic.

Conoscenze

Elastic Stack

Observability concepts

OpenTelemetry

Elastic Machine Learning

AIOps practices

Strumenti

Elasticsearch

Logstash

Kibana

Beats/Elastic Agent

APM

OpenTelemetry

ServiceNow

PagerDuty

Elastic AI Assistant

Descrizione del lavoro

Elastic AIOps Engineer Job Location: Bangalore Joining: Immediate

• 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