Senior Systems Engineer – Azure DevOps & GenAI

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 .