Senior Systems Engineer – Azure DevOps & GenAI

Role Details

• Experience: 5–8 years
  
• Primary Skills: Azure DevOps, Azure Cloud, CI/CD, Terraform, Bicep, ARM, AKS, Kubernetes
  
• AI Exposure: Azure AI Foundry, RAG, LLM APIs, Cognitive Search / Vector DBs
  
• OS: Windows & Linux
  
• Location/Mode/Budget :  Bengaluru/Hybrid/ Open (As per Market Standards)
  

Role Overview

We are looking for a Senior Systems Engineer with strong Azure DevOps and cloud infrastructure experience to design, automate, secure, and operate scalable Azure-based platforms. The role also requires practical exposure to GenAI application integration, including LLM APIs, RAG architecture, and AI-enabled backend systems.

Key Responsibilities

• Architect and build scalable, secure cloud infrastructure on Azure.
  
• Design and maintain advanced CI/CD pipelines with automation and quality gates.
  
• Automate infrastructure using Terraform, Bicep, ARM, and YAML.
  
• Deploy and manage AKS clusters and containerized workloads.
  
• Optimize systems for availability, performance, scalability, and cost efficiency.
  
• Build backend services using Azure-native components.
  
• Support secure production deployments and troubleshooting.
  
• Integrate GenAI applications using LLM APIs and RAG-based architectures.
  
• Mentor junior engineers and support technical best practices.
  

Required Skills

• 5–8 years of experience in systems engineering, DevOps, or cloud engineering.
  
• Strong hands-on experience with Azure architecture and Azure DevOps.
  
• Expertise in CI/CD, infrastructure automation, and production deployment practices.
  
• Experience with Terraform, Bicep, ARM templates, and YAML pipelines.
  
• Hands-on experience deploying and managing AKS / Kubernetes in production.
  
• Strong understanding of cloud networking, security, IAM, and troubleshooting.
  
• Experience administering both Windows and Linux systems.
  
• Familiarity with Azure AI Foundry, RAG architecture, Cognitive Search, vector databases, and LLM API integration.
  

Nice to Have

• Experience with AI agents and tool-calling workflows.
  
• Working knowledge of MCP integration approaches.
  
• Azure / Kubernetes / DevOps certifications.
  
• Exposure to enterprise AI-enabled platforms.
  

Preferred Candidate Profile

The ideal candidate will be a strong Azure DevOps / Systems Engineer with hands-on experience in Azure cloud infrastructure, CI/CD, Terraform, AKS, security, networking, Windows/Linux administration, and exposure to GenAI application integration.