Infrastructure Automation Engineer (AIOps & Agentic AI)

Role Overview

The Infrastructure Automation Engineer develops and deploys next-generation observability, AIOps, and Agentic AI automation solutions. This role enhances Site Reliability Engineering (SRE) capabilities by driving predictive diagnostics, self-healing workflows, and intelligent event correlation across enterprise infrastructure and applications.

Key Responsibilities

• AIOps & Agentic AI Workflows: Design and operationalize agentic AI workflows and scripts (Python, LangGraph) to automate operational diagnostics, event correlation, and auto-remediation.
• Infrastructure & CI/CD Automation: Provision and manage infrastructure using automation frameworks while integrating AIOps components into CI/CD pipelines via GitHub for continuous validation and deployment.
• Observability & Reliability: Implement event correlation across metrics, logs, and traces to enable proactive incident prevention, root-cause transparency, and automated incident response.
• SRE Culture & Governance: Codify SRE practices into the delivery lifecycle, maintain automated runbooks, and mentor team members on AI-driven automation standards.

Competencies and Qualifications

• Technical Background: Qualification in Computer Science, Information Technology, or equivalent practical experience.
• AIOps & Scripting: Hands-on experience developing AIOps and Agentic AI workflows using Python, LangGraph, or equivalent frameworks.
• Infrastructure & CI/CD: Experience with infrastructure automation tools, version control (GitHub), and CI/CD pipeline integration.
• Observability & SRE: Practical knowledge of full-stack observability (metrics, logs, traces), event correlation, and SRE frameworks for incident reduction.
• Collaboration & Communication: Strong interpersonal and communication skills to collaborate effectively with cross-functional engineering and operational teams.
• Certifications: Python/AI, Cloud DevOps (AWS/Azure), GitHub, SRE, or ITIL certifications are advantageous.