Site Reliability Engineer

SRE / AIOps Engineer

Experience

4–8 Years

Location

UAE – Dubai / Abu Dhabi

Employment Type

Full-Time / Contract

Work Mode

Onsite / Hybrid – As per client requirement

Role Overview

We are looking for an experienced SRE / AIOps Engineer to ensure the reliability, availability, scalability, and performance of enterprise applications and cloud infrastructure.

The ideal candidate should have strong hands-on experience in Site Reliability Engineering, cloud platforms, Kubernetes, observability, monitoring, automation, incident management, and CI/CD. Exposure to AIOps, machine learning-based anomaly detection, predictive monitoring, and automated incident remediation will be highly preferred.

Key Responsibilities

• Design and implement highly available, scalable, and resilient infrastructure and applications.
• Establish and manage Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Service Level Agreements (SLAs).
• Monitor application and infrastructure health, performance, availability, and capacity.
• Implement comprehensive observability solutions across applications, infrastructure, networks, and cloud environments.
• Develop dashboards, alerts, metrics, logs, and distributed tracing solutions.
• Identify performance bottlenecks and conduct root-cause analysis.
• Automate incident detection, diagnosis, and remediation.
• Implement AIOps capabilities to identify anomalies, correlate events, and reduce operational noise.
• Develop automated workflows for recurring operational and infrastructure tasks.
• Support production incidents and participate in on-call / 24x7 support when required.
• Conduct post-incident reviews and implement corrective and preventive actions.
• Improve system reliability and reduce Mean Time to Detect (MTTD) and Mean Time to Recovery (MTTR).
• Implement capacity planning, performance engineering, and disaster-recovery strategies.
• Work closely with Development, DevOps, Cloud, Security, and Infrastructure teams.
• Implement Infrastructure as Code and configuration automation.
• Build and maintain CI/CD pipelines for reliable and repeatable deployments.
• Continuously identify opportunities to improve system reliability through automation and AI.

Mandatory Skills

• 4–8 years of experience in SRE / DevOps / Cloud Engineering.
• Strong experience with Linux/Unix systems.
• Strong experience with AWS, Azure, or GCP.
• Hands-on experience with Kubernetes and Docker.
• Strong experience with monitoring and observability tools.
• Experience with Prometheus and Grafana or equivalent.
• Experience with centralized logging platforms such as ELK / OpenSearch.
• Experience with CI/CD tools such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps.
• Strong scripting/programming skills in Python, Bash, or PowerShell.
• Experience with Terraform / Infrastructure as Code.
• Strong understanding of networking, cloud infrastructure, and distributed systems.
• Experience with incident management and root-cause analysis.
• Good understanding of SLI, SLO, SLA, availability, latency, scalability, and reliability concepts.

Observability

Experience with one or more:

• Prometheus
• Grafana
• OpenTelemetry
• Splunk
• ELK / Elastic Stack
• OpenSearch
• Datadog
• Dynatrace
• New Relic
• AppDynamics

Knowledge of metrics, logs, traces, distributed tracing, and application performance monitoring (APM) is preferred.

AIOps Capabilities

Candidates with hands-on experience in the following will be preferred:

• AI-driven event correlation
• Automated anomaly detection
• Predictive monitoring
• Intelligent alerting
• Noise reduction
• Automated incident classification
• Root-cause analysis using AI
• Predictive capacity planning
• Automated remediation
• AI-assisted troubleshooting
• IT operations automation

Cloud Technologies

AWS

• EC2
• EKS
• CloudWatch
• Lambda
• S3
• IAM
• Auto Scaling
• CloudFormation

Azure

• Azure Monitor
• AKS
• Application Insights
• Azure Automation
• Log Analytics
• Azure DevOps

GCP

• GKE
• Cloud Monitoring
• Cloud Logging
• Cloud Trace
• Cloud Operations Suite

Kubernetes & Containerization

Strong understanding of:

• Kubernetes architecture
• EKS / AKS / GKE
• Docker
• Helm
• Kubernetes monitoring
• Resource management
• Auto-scaling
• Health checks
• Service discovery
• Kubernetes networking
• Container troubleshooting

Infrastructure as Code & Automation

Experience with:

• Terraform
• Ansible
• CloudFormation / ARM / Bicep
• Python
• Bash / PowerShell
• Git
• GitOps
• Argo CD

Incident & Reliability Management

Experience with:

• Incident response
• Problem management
• Root Cause Analysis (RCA)
• Disaster Recovery
• Business Continuity
• Capacity planning
• Performance engineering
• Change management
• Production support
• On-call operations

Good-to-Have Skills

• AIOps platforms such as Dynatrace Davis, Moogsoft, BigPanda, Splunk ITSI, or similar.
• OpenTelemetry.
• ServiceNow ITOM / ITSM.
• Kafka and distributed messaging systems.
• Microservices architecture.
• Service mesh technologies such as Istio.
• Chaos Engineering.
• FinOps / cloud cost optimization.
• DevSecOps.
• AI/ML fundamentals.
• Experience integrating LLMs into IT operations.
• Knowledge of MLOps / LLMOps.
• Experience with large-scale enterprise environments.

Certifications – Preferred

• AWS Certified DevOps Engineer
• Microsoft Azure DevOps Engineer
• Google Professional Cloud DevOps Engineer
• Certified Kubernetes Administrator (CKA)
• Certified Kubernetes Application Developer (CKAD)
• Certified Kubernetes Security Specialist (CKS)
• HashiCorp Terraform certification
• ITIL certification
• SRE / DevOps certifications

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline

Desired Candidate Profile

Candidate Profile

The ideal candidate should:

• Have strong troubleshooting and analytical capabilities.
• Be comfortable working with complex distributed systems.
• Have a strong automation mindset.
• Understand reliability and availability engineering principles.
• Be able to work effectively during production incidents.
• Have strong communication and stakeholder-management skills.
• Be comfortable working in a fast-paced enterprise environment.
• Demonstrate an interest in using AI and automation to improve IT operations.