Description

You will design, build, and operate intelligent, automated reliability solutions across production environments using AI-driven observability and automation practices.

This role is hybrid.

Responsibilities

• Implement and optimize monitoring with Dynatrace, Splunk, and Moogsoft to detect anomalies and correlate events.
• Design AI-powered workflows for incident detection, root cause analysis, and automated remediation.
• Configure PagerDuty for intelligent alerting and build self-healing automation using Ansible, Python, and GitHub Actions.
• Apply SRE principles including SLOs, SLIs, error budgets, and chaos testing to improve system reliability.
• Build CI/CD pipelines with GitHub Actions that integrate observability signals and automated rollback workflows.

Required Skills

• 10+ years of experience in Site Reliability Engineering or DevOps roles.
• Hands-on expertise with Dynatrace (including Davis AI), Splunk (ITSI, ML Toolkit), and Moogsoft AIOps.
• Proficiency in Python scripting for automation and tooling development.
• Experience configuring PagerDuty for incident response and alerting policies.
• Strong command of Ansible for infrastructure automation and configuration management.
• Skilled in using Git and GitHub Actions to build and maintain automated pipelines.
• Deep understanding of distributed systems, cloud infrastructure, and reliability engineering principles.

Preferred Skills

• Experience with Red Hat OpenShift and containerized environments (Kubernetes, Docker).
• Exposure to LLM-based automation or generative AI for operational workflows.
• Background in building or integrating with ChatOps frameworks and event-driven architectures.

Key Skills

Education

Any Graduate