An AI Cloud Engineer is responsible for building and managing the cloud infrastructure that powers AI and machine learning systems.

They bridge data science and DevOps by deploying intelligent workflows, maintaining auto-scaling compute clusters, and integrating enterprise systems with large language models (LLMs) and advanced AI platforms.

Core Responsibilities :

- Model Deployment & MLOps : Deploy pre-trained AI/ML models into production environments using cloud-native platforms (AWS, Azure, GCP).

- Infrastructure Management : Architect and maintain auto-scaling GPU/TPU clusters and cloud infrastructure for highly intensive AI workloads.

- Pipeline Orchestration : Manage end-to-end data pipelines for real-time and batch inference, prompt engineering, and context retrieval (RAG).

- Monitoring & Optimization : Continuously track AI model performance, latency, and system resource utilization while implementing cost-effective scaling strategies

Candidate's Profile :

- BE/BTECH, MCA/BCA with Min 5+ Years' experience in in AI / cloud delivery Experience with LLM-based solutions, orchestration / workflow-based implementations, APIs, and cloud-native development

- Ready for 6 to 12 months contract role in Bangalore, Hyderabad and Pune in Hybrid mode

- Can join within 15 days

Essential Skills :

- Cloud Platforms : Deep hands-on expertise in major cloud environments like AWS, Azure, or Google Cloud.

- Container Orchestration : Strong proficiency with Docker and Kubernetes for intelligent application packaging and scaling.

- Programming Languages : Proficiency in Python, Scala, or Go for automation and building backend API services.

- Infrastructure as Code (IaC) : Experience using tools such as Terraform, Pulumi, or native cloud frameworks to spin up environments