Site Reliability Engineer (SRE) – AI & Cloud Infrastructure

·   Design, implement, and manage highly available, scalable, and secure cloud infrastructure on AWS.

·   Build and maintain an end-to-end observability platform using Open Telemetry, Grafana, Datadog, CloudWatch, and related tools.

·   Implement AIOps capabilities, including:

·   LLM-assisted incident triage

·   AI-powered root cause analysis

·   ML-driven forecasting and anomaly detection

·   Intelligent alert correlation and noise reduction

·   Lead production incident management, on-call response, postmortems, and Root Cause Analysis (RCA).

·   Automate operational workflows using Infrastructure as Code (Terraform/CloudFormation) and CI/CD pipelines.

·   Drive infrastructure rightsizing, capacity planning, utilization analysis, and cloud cost optimization.

·   Build dashboards, SLOs, SLIs, and error budgets to improve service reliability.

·   Develop automation scripts using Python, Bash, or Go to eliminate manual operational tasks.

·   Monitor application and infrastructure health while ensuring high uptime and service performance.

·   Collaborate with Development, DevOps, Security, Platform Engineering, and Product teams across multiple time zones.

·   Establish operational best practices for monitoring, incident response, disaster recovery, and resilience engineering.

·   Maintain Linux-based production systems and troubleshoot OS, networking, storage, and performance issues.

·   5–8 years of experience in Site Reliability Engineering, DevOps, or Cloud Infrastructure Engineering.

·   Strong experience with AWS services including EC2, ECS/EKS, Lambda, VPC, IAM, CloudWatch, RDS, Route 53, S3, and Auto Scaling.

·   Hands-on experience with Open Telemetry, Grafana, Datadog, Prometheus, or similar monitoring platforms.

·   Strong knowledge of Linux administration, networking, system performance tuning, and troubleshooting.

·   Experience with Infrastructure as Code using Terraform or CloudFormation.

·   Proficiency in scripting using Python, Bash, or Go.

·   Experience with Kubernetes and containerized workloads.

·   Strong understanding of CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI, etc.).

·   Experience leading incident management, production support, and RCA processes.

·   Knowledge of SRE principles including SLIs, SLOs, and Error Budgets.

·   Experience implementing monitoring, logging, alerting, and observability frameworks.

·   Strong analytical, troubleshooting, and communication skills.

Preferred Qualifications

·   Experience building or implementing AIOps solutions.

·   Exposure to Large Language Models (LLMs) for operational automation.

·   Experience with machine learning-based forecasting or anomaly detection.

·   Hands-on experience administering Adobe Experience Manager (AEM).

·   Experience managing Cloudflare CDN, WAF, DNS, and caching strategies.

·   Knowledge of FinOps, cloud cost optimization, and capacity planning.

·   AWS Solutions Architect, DevOps Engineer, or Kubernetes certifications are a plus.