Senior Site Reliability Engineer
acquirex
Job Description
1. Incident Response & On-Call Ownership
· Participate in 24/7 on-call rotation for production systems.
· Rapidly diagnose, mitigate, and resolve high-severity production incidents.
· Lead Root Cause Analysis (RCA) and post-mortem documentation.
· Implement corrective and preventive actions to avoid recurrence.
· Drive improvements in Mean Time to Recovery (MTTR).
· Maintain and improve SLAs, SLOs, and reliability objectives.
2. Reliability Engineering & SRE Practices
· Implement and champion Site Reliability Engineering (SRE) best practices.
· Define, measure, and improve SLIs, SLOs, SLAs, and Error Budgets.
· Engineer solutions to eliminate repetitive operational work (toil reduction).
· Conduct reliability reviews and capacity planning exercises.
· Improve system redundancy, failover strategies, and disaster recovery readiness.
· Continuously improve service availability, latency, and operational excellence.
3. Cloud & Infrastructure Engineering
· Design, manage, and optimize infrastructure on Microsoft Azure (Mandatory).
· Manage Azure Virtual Machines, Networking, Storage, IAM, Azure Monitor, and cloud-native services.
· Experience with AWS services such as EC2, S3, RDS, IAM, VPC, and CloudWatch is preferred.
· Exposure to Google Cloud Platform (GCP) is a plus.
· Administer and optimize Kubernetes clusters and containerized workloads.
· Manage Helm deployments and Kubernetes-based applications.
· Implement Infrastructure as Code (Terraform preferred).
· Support Git-based workflows using GitHub, GitLab, or Azure Repos.
4. Monitoring, Observability & Performance Engineering
· Design and implement observability solutions using OpenTelemetry, Prometheus, Grafana, Datadog, CloudWatch, and Azure Monitor.
· Build and maintain distributed tracing frameworks using OpenTelemetry.
· Establish monitoring based on Golden Signals:
· Latency
· Traffic
· Errors
· Saturation
· Design symptom-based alerting focused on user impact.
· Analyze performance bottlenecks and optimize application and infrastructure performance.
· Improve logging, tracing, and monitoring strategies across distributed systems.
5. AI & Cloud-Native Workloads (Good to Have)
· Support deployment and operations of Azure AI Services and AI Foundry solutions.
· Assist in infrastructure design for RAG (Retrieval-Augmented Generation) workloads.
· Ensure scalability, reliability, and observability of AI/ML systems in production.
6. Security & Compliance
· Apply cloud security best practices including IAM, network segmentation, and secrets management.
· Support vulnerability remediation and security initiatives.
· Collaborate with development and security teams to meet compliance requirements.