HPE

AIOps Engineer

Location
Bengaluru
Work mode
Onsite
Experience
2–5 yrs exp
Pay
₹12–20 LPA (Est.)
Type
Full-time job, AI & ML
Added
30 October 2026

About this role

This role sits in HPE's engineering organisation in Bengaluru and is an onsite position. The engineer builds monitoring and incident response workflows that span cloud and on-premises systems. Day to day it involves building data pipelines for logs, metrics and events, developing predictive models to catch anomalies and outages, and automating remediation runbooks. The person works closely with DevOps, Site Reliability and security teams. It suits someone with a few years of IT operations or reliability experience who wants to apply machine learning to operations.

HPE is hiring for AIOps Engineer, a full-time role based in Bengaluru (onsite).

Who can apply: 2–5 yrs exp. Skills: Python, Splunk, Datadog, Prometheus, Grafana, Cloud operations, ServiceNow.

Hirastra checked that this opening is live. Apply directly through the official posting; applying is always free.

What you'll do

  • Design and maintain intelligent monitoring and incident response workflows across cloud and on-premises systems
  • Build and optimize data pipelines that collect, normalize and enrich logs, metrics and events
  • Develop and deploy predictive models to detect anomalies, forecast outages and reduce mean time to resolution
  • Automate remediation runbooks and integrate alerting with service management platforms
  • Partner with DevOps, Site Reliability and security teams on platform performance, availability and governance

What you need

  • Bachelor's degree in Computer Science, Information Technology or a related field
  • 2-5 years of experience in IT operations, reliability engineering or platform engineering, including AI-driven operations or automation roles
  • Python for automation, data processing and operational tooling
  • Observability platforms such as Splunk, Datadog, Prometheus or Grafana
  • Cloud platform operations on Azure, AWS or Google Cloud
  • Machine learning model lifecycle and deployment practices, plus ITSM and orchestration tools such as ServiceNow, PagerDuty or Rundeck

Skills

  • Python
  • Splunk
  • Datadog
  • Prometheus
  • Grafana
  • Cloud operations
  • ServiceNow

"Est." = Hirastra's estimate based on market data, not an official figure.

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