Cloud Engineer (Azure + GCP + AI Enablement)

We are looking for a Cloud Engineer with strong 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