AI-Enabled Platform/SRE Engineer

Role: AI-Enabled Platform/SRE Engineer

Location:  Dallas, TX / Scottsdale, AZ (Hybrid)

Duration: Long Term Contract

Pay Rate: $55/hr on C2C

Note: 2nd round inperson 

Key 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-datacentre Kubernetes environments.
• Develop observability and monitoring capabilities using tools such as Splunk, Grafana, Datadog, and AppDynamics 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.

Core Technical Skills

• 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 Google Cloud Platform, Terraform, Helm, GitHub, 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, AppDynamics, 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.