Hybrid AI Ops Engineer - Cloud & On-Prem Observability

Hewlett Packard Enterprise Development LP; San Juan (PR); Hybrid; USD 110,000 - 170,000; Full time

Job summary

Hewlett Packard Enterprise is seeking an AI Ops Engineer to design and operate intelligent monitoring and automation across cloud and on‑premises environments. The role emphasizes building data pipelines, deploying predictive models, and automating remediation to improve reliability.

The position is hybrid, requiring office presence about 2 days per week, and involves collaboration with DevOps, SRE, and security teams to drive platform performance and governance.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 5-8 years of experience in IT operations, reliability engineering, platform engineering, or roles focused on AI-driven operations and automation.

Responsibilities

• Design and maintain intelligent monitoring and incident response workflows across both cloud and on-premises systems.
• Build and optimize data pipelines to collect, normalize, and enrich logs, metrics, and events for operational analytics.
• 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 to enhance system reliability.
• Collaborate with DevOps, Site Reliability, and security teams to improve platform performance, availability, and operational governance.

Skills

Python for automation

AI-driven operations

Education

Bachelor’s degree in Computer Science/ Information Technology or related field

5-8 years IT operations/reliability/ platform engineering experience

Tools

Splunk

Datadog

Prometheus

Grafana

Azure

AWS

Google Cloud

ServiceNow

PagerDuty

Rundeck

Job description

Hewlett Packard Enterprise is seeking an AI Ops Engineer to design and operate intelligent monitoring and automation across cloud and on‑premises environments. The role emphasizes building data pipelines, deploying predictive models, and automating remediation to improve reliability.

The position is hybrid, requiring office presence about 2 days per week, and involves collaboration with DevOps, SRE, and security teams to drive platform performance and governance.