AI Ops Engineer
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Overview
Job Description
Job Title: AI Ops EngineerWork Location: Dallas/TX , Bellevue/WA
Job Summary
We are seeking an experienced AI Ops Engineer to design and implement an Agentic AI framework for cloud infrastructure and application operations. The ideal candidate will have hands-on experience building and deploying AI agents and will use AI-driven automation to monitor, maintain, troubleshoot, and support cloud-based solutions.
The candidate should have a strong understanding of AI agents, cloud technologies, Azure, Kubernetes, APIs, and enterprise application integration. Experience with MuleSoft and REST APIs is highly desirable.
Key Responsibilities
Design and develop an Agentic AI framework for monitoring, maintaining, and supporting cloud infrastructure and applications.
Build, configure, and deploy AI agents capable of performing operational and support tasks autonomously.
Develop AI-driven solutions for infrastructure monitoring, incident detection, troubleshooting, and remediation.
Integrate AI agents with cloud infrastructure, applications, monitoring tools, APIs, and enterprise systems.
Work with Microsoft Azure services and cloud-native technologies to build scalable AI Ops solutions.
Leverage Kubernetes for container orchestration, application deployment, monitoring, and operational automation.
Develop and integrate REST APIs to enable communication between AI agents, applications, and enterprise platforms.
Work with MuleSoft and enterprise integration technologies where required.
Design workflows that enable AI agents to analyze operational information and recommend or execute appropriate actions.
Implement automation for repetitive infrastructure and application support activities.
Collaborate with Cloud Engineers, DevOps, SRE, Application Development, and Architecture teams.
Mandatory Skills
Hands-on experience building and deploying AI Agents / Agentic AI solutions.
Strong understanding of AI agent frameworks, agent workflows, tools, and orchestration.
Experience developing AI-driven automation for infrastructure or application operations.
Strong programming/scripting and API integration skills.
Ability to design solutions where AI agents can interact with enterprise systems and cloud environments.
Good-to-Have Skills
Experience with Cloud technologies, preferably Microsoft Azure.
Hands-on experience with Microsoft Azure services.
Strong knowledge of Kubernetes and containerized applications.
Experience with MuleSoft and enterprise integration.
Strong knowledge of REST APIs and API-based integrations.
Experience with DevOps, SRE, cloud monitoring, and infrastructure automation.
Knowledge of observability, incident management, and automated remediation.
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.
