Site Reliability Engineer; SRE AI & Automation

Site Reliability Engineer (SRE) – AI & Automation

Our client, an IT Services and Consultant company, is looking for a Site Reliability Engineer (SRE) – AI & Automation for their Dallas, TX / Scottsdale, AZ / Hybrid location.

Responsibilities:

• Build automation and operational tools using Java, Python, and Node.js to improve efficiency, scalability, and platform operations.
• Leverage AI and Generative AI technologies (Gemini, Llama, Mistral, Qwen, etc.) to automate alert analysis, incident response, operational workflows, and runbook execution.
• Implement API and microservices reliability solutions using Apigee/Apigee X, REST APIs, GraphQL gateways, traffic routing, canary deployments, and failover strategies.
• Manage Kubernetes platforms across GKE and Rancher RKE2, including cluster administration, performance tuning, and troubleshooting.
• Ensure platform reliability and high availability by supporting active-active deployments, disaster recovery readiness, and multi-datacenter Kubernetes environments.
• Develop observability and monitoring capabilities using tools such as Splunk, Grafana, Datadog, and App Dynamics to meet reliability and performance objectives.
• Drive SRE best practices and operational excellence by partnering with cross-functional teams to improve reliability, security, incident management, and continuous improvement.

Requirements:

• Site Reliability Engineering (SRE) – Reliability, availability, incident management, SLO/SLI monitoring, and operational excellence.
• Kubernetes Platform Engineering – 5+ years of strong hands-on experience with GKE and Rancher RKE2, multi-cluster management, troubleshooting, and performance optimization.
• Cloud & Infrastructure Automation – Strong experience in GCP, Terraform, Helm, Git Hub, CI/CD, and production-grade automation.
• Software Development – 5+ years of advanced programming skills in Python and Java (Node.js preferred for integrations and automation workflows).
• Observability & Monitoring – Splunk, Grafana, Datadog, App Dynamics, alerting, and platform health monitoring.
• API & Microservices Engineering – Apigee/Apigee X, REST APIs, GraphQL, traffic routing, canary deployments, and failover strategies.
• AI-Driven Operations (AIOps) – Applying LLMs such as Gemini, Llama, Mistral, and Qwen for alert analysis, incident triage, automation, and operational workflows.
• Years of
  
  Experience:
  
  14.00 Years of Experience

Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities