Site Reliability Engineer (SRE)

Nuvento LLC
Kansas City, MO, United States
about 1 month ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours

Tech stack

Artificial Intelligence Application Performance Management Microsoft Azure Bash Shell Continuous Integration DevOps Github Python (Programming Language) Log Analysis Windows PowerShell Reliability Engineering Azure DevOps Pipelines
+11 more
Datadog Cloud Monitoring Mttr Infrastructure Automation Frameworks Information Technology Bicep Virtual Agents Terraform Software Version Control Serverless Computing Pagerduty

Job description

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  • Deploy, configure, and manage Azure SRE Agent across production workloads to automate incident investigation, root cause analysis, and remediation workflows \n

  • Monitor production systems and respond to incidents in partnership with Azure SRE Agent, reviewing agent-proposed diagnoses and mitigations and approving actions per governance policy \n

  • Build and maintain runbooks, subagents, and agent hooks within Azure SRE Agent to automate common operational tasks and reduce manual toil \n

  • Connect Azure SRE Agent to observability, incident management, and source control tooling (Azure Monitor, Application Insights, Log Analytics, GitHub, PagerDuty, or similar) to enable end-to-end automated investigations \n

  • Define and maintain service level objectives (SLOs), service level indicators (SLIs), and error budgets for critical services, and use agent-driven insights to track and improve them \n

  • Establish and enforce tool permissions, hooks, and governance controls for AI agent actions to ensure safe, auditable automation with appropriate human approval gates \n

  • Analyze incident trends and agent-surfaced institutional knowledge to identify recurring issues and drive permanent fixes and reliability improvements \n

  • Participate in on-call rotation, leveraging Azure SRE Agent to accelerate triage, reduce mean time to detect/resolve (MTTD/MTTR), and minimize after-hours disruptions \n

  • Author and refine incident response plans, playbooks, and postmortem processes, incorporating agent-generated documentation and learnings \n

  • Partner with DevOps, Platform Engineering, and development teams to instrument applications and infrastructure for effective AI-driven monitoring and diagnostics \n

  • Continuously evaluate new Azure SRE Agent capabilities (connectors, private plugins, subagents) and pilot adoption to expand automated coverage \n

  • Contribute to Infrastructure as Code and automation scripts that support reliable, repeatable, and agent-manageable environments \n

Requirements

  • Bachelor’s degree in computer science, Information Technology, or a related field required, or equivalent professional experience \n

  • 5+ years of experience in Site Reliability Engineering, DevOps, or a related production operations role \n

  • Hands-on experience with Azure SRE Agent or comparable AI-powered incident response/observability tooling strongly preferred \n

  • Strong working knowledge of Azure cloud services, including AKS, App Service, Azure Functions, and Azure networking \n

  • Experience with observability and monitoring platforms (Azure Monitor, Application Insights, Log Analytics, or similar) \n

  • Practical understanding of SRE fundamentals, including SLOs/SLIs, error budgets, incident management, and blameless postmortems \n

  • Familiarity with CI/CD tooling such as Azure DevOps Pipelines and GitHub Actions \n

  • Experience with Infrastructure as Code tools such as Bicep or Terraform \n

  • Comfort working with AI agents and automation frameworks, including reviewing and approving AI-proposed remediations under governance controls \n

  • Strong scripting and automation skills (PowerShell, Bash, or Python) \n

  • Excellent troubleshooting skills and the ability to remain calm and methodical during production incidents, * Strong communication skills, with the ability to document findings clearly for both technical and non-technical audiences

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