Summary:
Develop and roll out new observability and automation solutions, driving increased demand for development capacity for Site Reliability Engineering (AIOps and Agentic AI).
Key Responsibilities:
AIOps & Agentic AI Engineering
- Develop Python and/or LangGraph scripts and agentic AI workflows to automateoperational tasks, diagnostics, and remediation.
- Build and integrate AIOps capabilities for predictive alerting, anomaly detection,and intelligent event correlation across infrastructure and applications
- Design and operationalise agentic AI solutions that augment incident response and reduce manual intervention.
- Develop self-healing and auto-remediation workflows driven by AI/ML and event correlation insights.
Infrastructure Automationand CI/CD
- Develop infrastructure automation to provision, configure, and manage systems in aconsistent, auditable manner.
- Manage automation and AI code through GitHub, applying version control, code review,and collaboration best practices.
- IntegrateAIOps and automation components into CI/CD pipelines for continuous testing,validation, and deployment.
Observability, Reliability& Collaboration
- Implement observability and event correlation across metrics, logs, and traces to enable proactive reliability management.
- Champion SRE frameworks and reliability practices, embedding AIOps into the delivery life cycle
- Collaborate with Application, Infrastructure, Cloud, and Cyber teams to enable predictive incident prevention and root-cause transparency
- Maintain documentation and runbooks, and mentor engineers on AIOps and automation best practices.
