ABOUT THE ROLE

We are hiring an AIOps Engineer to apply machine learning and analytics to IT operations — turning logs, metrics, traces and events into automated anomaly detection, root-cause analysis, incident prediction and self-healing across our client's cloud and platform estate.

WHAT YOU'LL DO

• Build ML models for anomaly detection, event correlation, alert-noise reduction and incident prediction across logs, metrics, traces and events.

• Implement automated root-cause analysis and self-healing / auto-remediation workflows.

• Integrate AIOps with observability stacks (Prometheus, Grafana, OpenTelemetry, ELK, Datadog, Dynatrace, Splunk) and ITSM (ServiceNow).

• Deploy and tune AIOps platforms (Moogsoft, BigPanda, Splunk ITSI) for alert correlation and reduction.

• Build capacity-forecasting and time-series models to pre-empt outages.

• Monitor model accuracy and drift; partner with SRE/on-call teams to reduce MTTR.

SKILLS & REQUIREMENTS

Must-have:
Python, Machine Learning (anomaly detection & time-series),



Observability & Telemetry (Prometheus/Grafana/OpenTelemetry/ELK/Datadog/Dynatrace/Splunk), Event Correlation & Root-Cause Analysis, ITSM (ServiceNow), Cloud Platforms (AWS/Azure/GCP), Incident Management / SRE

Good-to-have:
AIOps platforms (Moogsoft, BigPanda, Splunk ITSI), Kafka / streaming data, log analytics, Kubernetes monitoring, capacity forecasting, scikit-learn / statistical modelling, ChatOps, MLOps

Certifications:
Cloud certification (AWS/Azure/GCP) and/or an observability cert (e.g. Datadog) preferred.

WHAT WE LOOK FOR

• 5+ years in SRE/DevOps/ITOps or ML with hands-on AIOps or ML-for-operations experience.

• Solid Python and applied ML (anomaly detection, forecasting) skills.

• Deep understanding of observability, incident management and reducing MTTR.

How to apply:
Apply via LinkedIn or email your CV to
[email protected]
.

📌 AIOps Engineer (Bengaluru)
🏢 NLightN
📍 Bengaluru