AI Ops Engineer: Agentic AI for Cloud Automation

BlackCube Labs; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

BlackCube Labs seeks an AI Ops Engineer to design and deploy agentic AI systems for cloud and application operations, enabling autonomous decision-making, incident analysis, and remediation workflows.

You will collaborate with Cloud and Platform teams to deliver scalable AI-driven operations across Azure, Kubernetes, and enterprise environments, ensuring secure, observable, and automated processes.

Qualifications

• Must have experience designing and building agentic AI / AI agents and orchestration.
• LLM-based solution design and knowledge frameworks experience.
• Experience with Azure Cloud and Kubernetes environments.
• Experience with MuleSoft integrations and REST APIs.

Responsibilities

• Design and implement an Agentic AI framework for Cloud Infrastructure and Application Operations.
• Build and orchestrate AI agents for monitoring, diagnostics, knowledge retrieval, incident triaging, remediation, and automation.
• Develop knowledge frameworks using runbooks and enterprise docs.
• Integrate AI agents with enterprise platforms and tools via APIs.
• Enable AI-driven automation for cloud monitoring, observability, and operational intelligence.
• Collaborate with Cloud and Platform teams to architect scalable, secure AI-enabled solutions.
• Create reusable frameworks, accelerators, and governance for AI-based operations.
• Support Azure, Kubernetes, MuleSoft, and enterprise ecosystems.

Skills

Agentic AI

LLM-based design

AI-driven monitoring

AI Ops Knowledge

Enterprise cloud operations

Telecom/OSS domain

Tools

Azure Cloud

Kubernetes

MuleSoft

REST API integrations

Job description

BlackCube Labs seeks an AI Ops Engineer to design and deploy agentic AI systems for cloud and application operations, enabling autonomous decision-making, incident analysis, and remediation workflows.

You will collaborate with Cloud and Platform teams to deliver scalable AI-driven operations across Azure, Kubernetes, and enterprise environments, ensuring secure, observable, and automated processes.