AIOps/Automation Engineer
2 days ago
Job Title : AI Ops / Automation Engineer
Experience : 7 Years
Work Mode : Work from Office / Hybrid
Job Overview :
We are looking for an experienced AI Ops / Automation Engineer with strong expertise in IT operations automation, monitoring, and AI-driven incident management. The ideal candidate will have hands-on experience with AIOps platforms, DevOps/Cloud automation, and advanced scripting to streamline operations, improve system reliability, and reduce manual intervention.
Key Responsibilities :
- Design, develop, and implement AIOps and automation solutions to enhance IT operations efficiency.
- Integrate monitoring tools, observability platforms, and AIOps solutions for predictive incident detection and resolution.
- Automate repetitive operational tasks using Python, Ansible, Terraform, or equivalent tools.
- Implement event correlation, noise reduction, and root-cause analysis via AIOps platforms.
- Collaborate with DevOps, Cloud, and Infrastructure teams to define and implement automation strategies.
- Ensure scalability, resilience, and performance of production systems through automation.
- Build and maintain CI/CD pipelines with automated monitoring and remediation workflows.
- Drive adoption of ML/AI-based solutions to improve operational visibility and reduce MTTR (Mean Time to Resolution).
- Provide mentorship and technical guidance to junior engineers.
Must-Have Skills :
- 7 years of experience in IT Operations / Automation / DevOps roles.
- Hands-on experience with AIOps platforms (Moogsoft, Splunk ITSI, Dynatrace, New Relic, BigPanda, or equivalent).
- Strong expertise in scripting/programming (Python, Shell, PowerShell).
- Experience with Infrastructure as Code (IaC) tools such as Ansible, Terraform, or Puppet.
- Good knowledge of CI/CD pipelines, Kubernetes, Docker, and container orchestration.
- Proficiency in monitoring & observability tools : Prometheus, Grafana, ELK, Splunk, AppDynamics, Datadog.
- Strong understanding of incident management, root cause analysis, and ITIL practices.
- Cloud expertise : AWS, Azure, or GCP automation & monitoring.
- Excellent problem-solving skills, analytical mindset, and ability to work in fast-paced environments.
Good to Have :
- Exposure to Machine Learning concepts applied to operations (log analysis, anomaly detection, predictive analytics).
- Knowledge of service mesh (Istio, Linkerd) and cloud-native monitoring frameworks.
- Experience with security automation (SOAR, SIEM integration).
- Prior experience in leading automation initiatives or small teams.
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