Senior Systems Engineer – Azure DevOps & GenAI
Summary
Senior systems engineer (5–8 yrs) designing, automating, and operating secure Azure cloud platforms: CI/CD pipelines, infrastructure-as-code with Terraform/Bicep/ARM, and AKS workloads, plus integrating GenAI features via LLM APIs and RAG. Hybrid role based in Bengaluru.
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.