Design, automate, secure, and operate scalable Azure cloud infrastructure and platforms. Build CI/CD pipelines, automate infrastructure with Terraform, Bicep, ARM, and YAML, and manage production AKS and Kubernetes workloads. Optimize system availability, performance, scalability, and cost while supporting secure deployments and troubleshooting. Integrate GenAI applications using Azure AI Foundry, LLM APIs, RAG, Cognitive Search, and vector databases. Mentor junior engineers and promote technical best practices.
Senior Systems Engineer – Azure DevOps & GenAI
Role Details
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)
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.
- 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.
- 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.
- Experience with AI agents and tool-calling workflows.
- Working knowledge of MCP integration approaches.
- Azure / Kubernetes / DevOps certifications.
- Exposure to enterprise AI-enabled platforms.
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.
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