DevJobs

Senior Azure Platform & DevOps Engineer

Overview
Skills
  • PostgreSQL PostgreSQL
  • CI/CD CI/CD
  • Azure DevOps Azure DevOps
  • Azure Azure ꞏ 5y
  • Kubernetes Kubernetes
  • Networking Networking
  • Terraform Terraform
  • Entra ID
  • Key Vault
  • GitOps
  • Storage
  • cloud databases
  • AKS
  • workflow orchestration systems
  • Temporal
  • OpenTofu
  • OpenAI
  • observability tools
  • AI
  • model serving
  • ML infrastructure
  • Langfuse
  • GPU
  • Flux
  • Azure AI services
  • ArgoCD
  • AI Search
A fast-growing enterprise technology company is looking for a Senior Azure Platform & DevOps Engineer to join its core engineering team and take full ownership of its Azure cloud environment. The role is highly hands-on and involves designing, building, and operating a production-grade platform that supports AI agents, Kubernetes-based workloads, and large-scale workflow orchestration, with close collaboration alongside backend and AI engineers.

Responsibilities

  • Own the end-to-end Azure platform and ensure production reliability and scalability
  • Design and evolve cloud architecture supporting AI-driven, Kubernetes-based workloads
  • Build and maintain Infrastructure as Code and deployment automation
  • Lead CI/CD and GitOps processes across environments
  • Operate and improve production Kubernetes systems and observability stack
  • Drive security, governance, and cost optimization across the platform

Requirements:

  • 5+ years of experience in DevOps / Platform / Infrastructure engineering
  • Strong hands-on experience with Azure (AKS, Networking, Entra ID, Key Vault, Storage)
  • Deep Kubernetes expertise in production environments
  • Strong experience with Terraform or OpenTofu
  • Experience with CI/CD pipelines (Azure DevOps preferred)
  • Experience with GitOps tools (ArgoCD or Flux)
  • Strong knowledge of PostgreSQL and cloud databases
  • Ability to work independently with high ownership

Nice to Have

  • Experience with Temporal or workflow orchestration systems
  • Experience with AI/ML infrastructure or model serving
  • Experience with Azure AI services (OpenAI, AI Search)
  • Experience optimizing Kubernetes workloads for GPU/AI systems
  • Experience with observability tools such as Langfuse or similar
Gini-Apps