Executive-KDNI

KPMG · ✓ Verified company
📍 Bangalore, Karnataka, India · On-site · Full-time

About the role

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 • 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. • 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.