Azure AI Studio Expert - Cloud Infrastructure Management (8-14 yrs)

Urgent requirement for Azure AI Studio for Bangalore Location.

Experience : 8-14 Yrs

Job Location : Bangalore

Job Description :

Key Responsibilities :

Cloud Infrastructure Management :

- Design, deploy, and manage AI solutions on Azure AI Studio and Google Cloud Platform (GCP).

- Optimize cloud resources to ensure cost-effectiveness and high performance.

CI/CD Pipeline Development :

- Develop and maintain continuous integration and continuous deployment pipelines for AI applications.

- Automate deployment processes to streamline workflows and reduce time-to-market.

Hardware Integration :

- Manage and configure specialized hardware workstations including HP Fury Z8, Dell 7960 XCTO, and Nvidia GCX Studio A100.

- Ensure seamless integration between cloud services and on-premises hardware resources.

AI/ML Operations :

- Implement AI Ops, ML Ops, and RAG Ops practices to enhance the reliability and scalability of AI systems.

- Monitor system performance, troubleshoot issues, and implement improvements.

Collaboration and Support :

- Collaborate with cross-functional teams to understand requirements and deliver robust AI solutions.

- Provide technical support and guidance to team members regarding DevOps best practices and tools.

Security and Compliance :

- Ensure all deployments adhere to security standards and compliance regulations.

- Implement and maintain security protocols for both cloud and on-premises environments.

Qualifications :

Education :

Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred.

Experience :

- Proven experience as a DevOps Engineer, preferably within AI or machine learning environments.

- Strong expertise in Azure AI Studio and developing AI solutions on the Azure platform.

- Experience with Google Cloud Platform (GCP) in deploying and managing AI solutions.

Technical Skills :

- Proficiency with cloud services, including compute, storage, networking, and AI/ML tools on Azure and GCP.

- Hands-on experience with CI/CD tools such as Jenkins, GitLab CI, or Azure DevOps.

- Familiarity with containerization and orchestration technologies like Docker and Kubernetes.

- Knowledge of infrastructure as code (IaC) tools such as Terraform or Azure Resource Manager.

Experience with specialised hardware workstations :

1. HP Fury Z8

2. Dell 7960 XCTO

3. Nvidia GCX Studio A100

4. Understanding of AI Ops, ML Ops, and RAG Ops methodologies.

Soft Skills :

- Strong problem-solving skills and attention to detail.

- Excellent communication and teamwork abilities.

- Ability to manage multiple tasks and prioritize effectively in a fast-paced environment.

Preferred Qualifications :

- Certifications in Azure (e.g., Azure DevOps Engineer Expert) or Google Cloud (e.g., Professional DevOps Engineer).

- Experience with monitoring and logging tools such as Prometheus, Grafana, or Azure Monitor.

- Knowledge of scripting languages like Python, Bash, or PowerShell.

- Familiarity with version control systems, particularly Git.