Executive-KDNI As a DevOps professional in our team, you will play a pivotal role in designing, implementing, and managing the infrastructure and deployment pipelines that support our AI-driven applications. You will work closely with data scientists, AI researchers, and software engineers to ensure seamless integration and optimal performance of AI solutions.

Key responsibilities include: Cloud Infrastructure Management:

- Design, deploy, and manage AI solutions on Azure 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 on Azure DevOps and GitHub Actions.
- Develop and maintain automated code and security scan pipelines.
- 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.

Educational

Qualifications • Bachelor’s degree in Computer Science, Engineering, or a related field. Master’s degree preferred. Work Experience • 1-3 Years of Work Experience • Robust 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.
- Proven experience as a DevOps Engineer, preferably within AI or machine learning environments.

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 Azure DevOps or GitHub Actions or Jenkins.
- 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 Level Executive Level

📌 DevOps Engineer for AI and Cloud Infrastructure (Bengaluru)
🏢 KPMG India Services
📍 Bengaluru