Senior Cloud Engineer

Key Responsibilities

• Design and implement cloud architecture for AI/ML, LLM model deployment, monitoring, and scaling
• Deploy models using Docker, Kubernetes, and CI/CD pipelines across cloud environments on Azure or GCP
• Optimize AI model serving using tools like TensorFlow Serving, TorchServe, ONNX Runtime, Triton Inference Server, etc.
• Build and manage IaC using Terraform, or CloudFormation
• Implement security best practices, autoscaling, logging, monitoring (Prometheus/ Grafana/ ELK), and disaster recovery plans
• Collaborate with ML engineers to produce prototypes into resilient, cloud-native services
• Benchmark and tune deployments for low latency, high throughput, and cost optimization

Required Qualifications

• 8+ years of experience in cloud engineering, with 4+ years focused on AI/ML deployment at scale
• Strong hands-on expertise in Azure and GCP
• Proficient in Docker, Kubernetes, Helm, and serverless deployment models
• Solid understanding of ML frameworks (TensorFlow, PyTorch, scikit-learn) and model deployment workflows
• Experience in CI/CD tools (GitHub Actions, Jenkins, GitLab CI), scripting (Python, Bash), and API gateway management