We are looking for a Cloud Engineer with solid expertise in Azure and GCP, coupled with an AI-first mindset. The ideal candidate will be responsible for building, automating, and managing scalable cloud platforms while enabling cloud environments that support modern AI, GenAI, and data-driven applications.

This role requires hands-on experience in cloud infrastructure, DevOps, Kubernetes, automation, and security, along with exposure to AI platforms, MLOps, or Generative AI workloads.

Key Responsibilities

- Design, deploy, and manage secure, scalable cloud infrastructure across Azure and GCP.
- Implement Infrastructure as Code (IaC) using Terraform and automation tools.
- Build and support cloud-native platforms using Kubernetes, containers, and serverless services.
- Manage CI/CD pipelines and deployment automation.
- Collaborate with Data, AI, and Application teams to enable AI/ML and GenAI workloads.
- Implement cloud monitoring, observability, security, and governance frameworks.
- Optimize cloud performance, reliability, and cost.
- Support migration of on-premise applications to cloud environments.
- Enable AI-ready infrastructure for model deployment, inferencing, and data processing workloads.
- Ensure adherence to security, compliance, and operational best practices.

Required Skills

Cloud Platforms

- Hands-on experience with Microsoft Azure and Google Cloud Platform (GCP).
- Strong understanding of cloud networking, IAM, security, and governance.





- Experience with
- Azure Virtual Machines, VNets, Storage, AKS, Azure Monitor
- GCP Compute Engine, GKE, VPC, Cloud Storage, Cloud Monitoring

DevOps & Automation
- Terraform (Mandatory)
- GitHub Actions / Azure DevOps / Jenkins
- Docker & Kubernetes (AKS/GKE)
- Linux Administration
- Scripting using Python, Bash, or PowerShell

Monitoring & Security
- Prometheus, Grafana, Azure Monitor, Log Analytics
- Cloud Security, IAM, Secrets Management
- Disaster Recovery and High Availability architectures

AI & GenAI (Preferred)
- Understanding of AI/ML platforms and cloud AI services.

- Exposure to

- Azure AI Foundry

- Azure OpenAI

- Vertex AI

- Generative AI solutions

- LLMs and RAG architectures
- Vector Databases and AI Search

- MLOps / LLMOps concepts
- Experience supporting AI model deployment and inference workloads.
- Knowledge of AI governance, security, and responsible AI practices.

Preferred Qualifications
- Experience in multi-cloud environments.
- Exposure to Data Engineering or AI Engineering platforms.
- Understanding of Agentic AI and AI-driven automation frameworks.
- Experience with enterprise-scale cloud transformation initiatives.

Certifications (Good to Have)
- Microsoft Azure Administrator (AZ-104)
- Azure Solutions Architect (AZ-305)
- Google Associate Cloud Engineer
- Google Professional Cloud Architect
- Kubernetes (CKA/CKAD)
- Terraform Associate

📌 Cloud Engineer (Azure + GCP + AI Enablement) (Delhi)
🏢 IRIS SOFTWARE
📍 Delhi