Role Overview

The AI Operations & Platform Engineer is responsible for designing, building, and operating AI-powered operational solutions that improve infrastructure management, incident response, monitoring, automation, governance, and cloud operations. The role combines cloud engineering, infrastructure operations, automation, software development, and AI technologies to deliver intelligent operational capabilities across Azure and hybrid environments.

Responsibilities

AI Operations Engineering
- Build AI agents for incident investigation, root cause analysis, monitoring, alert triage, and operational automation.
- Develop agentic workflows using LangGraph, LangChain, Semantic Kernel, or equivalent.
Cloud & Infrastructure Engineering
- Design, deploy, and maintain Azure infrastructure solutions.
- Support hybrid cloud environments spanning Azure and on-premises infrastructure.
- Implement Infrastructure-as-Code using Terraform or Bicep.
Platform Engineering & Automation
- Develop automation solutions for provisioning, deployment, compliance, governance, and operational management.
- Build self-service infrastructure and platform capabilities.
Observability & Operational Intelligence
- Implement monitoring, logging, tracing, and observability solutions.
- Build operational dashboards and automated investigation capabilities.
DevOps & Delivery Enablement
- Design and maintain Azure DevOps pipelines and deployment frameworks.
- Support Git-based development practices and CI/CD.
Governance & Security
- Implement Azure Policies, Defender for Cloud controls, and governance frameworks.
- Ensure AI solutions align with enterprise security and operational requirements.

Requirements

Mandatory Skills:

LangGraph, LangChain, Azure AI Foundry, Azure OpenAI
Vector databases and RAG architectures
OpenTelemetry
AKS and Container Apps

Preferred Skills:

Strong Azure infrastructure experience
Azure networking, identity, security, monitoring, and governance
Azure DevOps and CI/CD pipelines
PowerShell and Python
Bicep
Understanding of AI, LLMs, AI Agents, and automation
API integration and cloud services
Strong troubleshooting and root cause analysis skills

Experience:

Total 7+ years of experience in Azure Infra and AI Automation.
5+ years in Azure Infrastructure, Cloud Operations, Platform Engineering, or DevOps.
2+ years in automation and software development.
Experience building operational tools, dashboards, or automation platforms.
Exposure to AI, LLMs, AI agents, or AI-powered operational use cases.