System Admin/Engineer

Dew Software, a prominent player in the Digital Transformation industry, is currently seeking a skilled and adaptable System Admin/Engineer to join our team. As a System Admin/Engineer at Dew Software, you will play a crucial role in ensuring the stability, security, and optimum performance of our clients' IT systems. You will have the opportunity to work on a variety of projects and collaborate with cross-functional teams to design, implement, and maintain robust infrastructure solutions.

Responsibilities

• Maintain and monitor the stability, security, and performance of clients' IT systems.
• Install, configure, and maintain server operating systems, hardware, and software.
• Troubleshoot and resolve hardware, software, and network issues.
• Manage user accounts, permissions, and access rights.
• Collaborate with cross-functional teams to design and implement infrastructure solutions.
• Create and maintain documentation related to system configurations and procedures.
• Stay up-to-date with emerging technologies and industry best practices.

• Good knowledge of Manage Engine UEMS with minimum of 2-4 years of experiene.
• Expert in Microsoft OS (Windows 10, 11).
• Expert in Misc Hardware related troubleshooting
• Work with MTT on daily basis to identify machines for SP upgrade, hands and feet support.
• Work with IT security on daily basis to fix any IT security or network issue.
• Work with Firoz daily to execute the project. Troubleshoot independently for any OS, or hardware issue.
• Work with OEM for hardware issues Work with Microsoft for OS issues.
• Work with ManageEngine for application related issues.
• Work with the Server team for domain, GP related issues.

• Azure Infrastructure Experience: Proficiency in managing Azure infrastructure components, including virtual machines, storage, and networking, to support AI model development and deployment.
• CI/CD Pipeline Experience: Experience with Continuous Integration/Continuous Deployment (CI/CD) pipelines, including the automation of model deployment processes.
• Containerization in the Cloud: Strong knowledge of containerization technologies in the cloud, such as Docker and Kubernetes, for efficient deployment and scaling of machine learning models.
• Machine Learning Expertise: Proficient in building and optimizing machine learning models, with a deep understanding of various ML algorithms and frameworks.
• Programming Skills: Proficiency in programming languages commonly used in machine learning, such as Python and libraries like TensorFlow and PyTorch.
• Data Management: Experience in data preprocessing, feature engineering, and data pipeline development for machine learning.
• Collaborative Team Player: Excellent communication skills and the ability to work collaboratively with cross-functional teams, including AI engineers and SREs.
• Documentation: Effective documentation skills to maintain clear and organized records of models, infrastructure configurations, and incident responses.