Responsibilities:
The interns will learn the following:
Assist in setting up and maintaining CI/ CD pipelines for application and AI workloads
Support infrastructure provisioning and automation using scripts and Infrastructure-as-Code concepts
Help deploy, monitor, and maintain applications, APIs, and AI models in development and test environments
Assist in containerization using Docker and orchestration concepts such as Kubernetes
Support system monitoring, logging, and basic performance troubleshooting
Collaborate with development and data teams to enable smooth DevOps workflows
Assist in integrating AI/ML components into applications and pipelines
Document deployment processes, configurations, and operational procedures
Participate in Agile ceremonies and sprint-based delivery activities
Qualifications:
Currently pursuing a degree in Computer Science, Engineering, Data Science, AI, or related fields (in the last semester and internship is required before graduation). You can start an employment after internship completion
Basic understanding of software development and SDLC concepts
Familiarity with Linux fundamentals and command-line usage
Basic scripting knowledge (e.g., Python, Bash, or similar)
Understanding of cloud concepts (AWS, Azure, or GCP – academic exposure acceptable)
Interest in DevOps, automation, and AI technologies
Willingness to learn, experiment, and work in a team-based environment
Preferred Skills:
Exposure to CI/ CD tools (GitHub Actions, GitLab CI, Jenkins, or Azure DevOps)
Basic knowledge of Docker and containerization concepts
Familiarity with Infrastructure as Code tools (Terraform, ARM, or similar)
Exposure to AI / Machine Learning concepts (model training, inference, MLOps basics)
Notes:
Internship and Employment Opportunity
The Company offers internship placements ranging from six (6) to twelve (12) months. This program is primarily intended for students whose academic program designates the final semester for internship and permits an extension of the internship period, subject to approval by the respective university.
Prior to application, applicants are advised to ensure that any required extension of the internship duration is approved by their university in accordance with its applicable policies and procedures.
Upon satisfactory completion of the internship, candidates may be considered for full-time employment opportunities, subject to the Company’s recruitment policies and business requirements. In such cases, eligible candidates may transition directly into employment without the need to resume academic study, in accordance with their academic program structure.
#LPS
The interns will learn the following:
Assist in setting up and maintaining CI/ CD pipelines for application and AI workloads
Support infrastructure provisioning and automation using scripts and Infrastructure-as-Code concepts
Help deploy, monitor, and maintain applications, APIs, and AI models in development and test environments
Assist in containerization using Docker and orchestration concepts such as Kubernetes
Support system monitoring, logging, and basic performance troubleshooting
Collaborate with development and data teams to enable smooth DevOps workflows
Assist in integrating AI/ML components into applications and pipelines
Document deployment processes, configurations, and operational procedures
Participate in Agile ceremonies and sprint-based delivery activities
Qualifications:
Currently pursuing a degree in Computer Science, Engineering, Data Science, AI, or related fields (in the last semester and internship is required before graduation). You can start an employment after internship completion
Basic understanding of software development and SDLC concepts
Familiarity with Linux fundamentals and command-line usage
Basic scripting knowledge (e.g., Python, Bash, or similar)
Understanding of cloud concepts (AWS, Azure, or GCP – academic exposure acceptable)
Interest in DevOps, automation, and AI technologies
Willingness to learn, experiment, and work in a team-based environment
Preferred Skills:
Exposure to CI/ CD tools (GitHub Actions, GitLab CI, Jenkins, or Azure DevOps)
Basic knowledge of Docker and containerization concepts
Familiarity with Infrastructure as Code tools (Terraform, ARM, or similar)
Exposure to AI / Machine Learning concepts (model training, inference, MLOps basics)
Notes:
Internship and Employment Opportunity
The Company offers internship placements ranging from six (6) to twelve (12) months. This program is primarily intended for students whose academic program designates the final semester for internship and permits an extension of the internship period, subject to approval by the respective university.
Prior to application, applicants are advised to ensure that any required extension of the internship duration is approved by their university in accordance with its applicable policies and procedures.
Upon satisfactory completion of the internship, candidates may be considered for full-time employment opportunities, subject to the Company’s recruitment policies and business requirements. In such cases, eligible candidates may transition directly into employment without the need to resume academic study, in accordance with their academic program structure.
#LPS