Intern

About the Role

The Intern works on projects in the Monitoring solutions Software/ systems / test /Reliability Engineering teams. This internship offers hands-on experience in building intelligent, scalable, and cloud-ready applications using Java Spring Boot, Angular, WebSockets, Docker, Linux, and modern front-end technologies—augmented by AI-assisted development practices, automation, and data-driven decision making. Interns will work in a real-world Systems engineering environment, leveraging AI tools and best practices to improve developer productivity, software quality, and system reliability.

Key Responsibilities

• Assist in designing and developing AI-enabled full-stack applications using Spring Boot (backend) and Angular (frontend).
• Build and integrate RESTful APIs and real-time communication using WebSockets.
• Apply AI-assisted coding and debugging tools to accelerate development and improve code quality.
• Develop user-centric, responsive web interfaces using HTML, CSS, and JavaScript.
• Work in Linux-based environments for application development, testing, and deployment.
• Implement and manage Docker-based containerized deployments to ensure scalability and portability.
• Support intelligent automation for testing, deployment, and monitoring (CI/CD exposure).
• Debug, analyze, and troubleshoot technical issues using structured problem-solving approaches.
• Collaborate in agile ceremonies and contribute to engineering discussions driven by data and insights.
• Follow best coding practices and maintain well-documented, maintainable, and testable code.

Requirements & Tech Stack

• Strong programming fundamentals in Java with familiarity in Spring Boot.
• Knowledge of Angular or modern JavaScript/TypeScript frameworks.
• Basic understanding of real-time systems (WebSockets or event-driven architectures).
• Hands-on experience with Linux commands and shell scripting.
• Proficiency in HTML, CSS, and JavaScript for front-end development.
• Understanding of RESTful services and backend–frontend integration.
• Basic exposure to Docker and containerization concepts.
• Strong analytical thinking and problem-solving skills.
• Curiosity and eagerness to learn AI-assisted engineering practices.
• Effective communication and teamwork skills.

Preferred Qualifications

• Experience with Git and version control workflows.
• Familiarity with database systems such as MySQL or PostgreSQL.
• Exposure to CI/CD pipelines, automation, or cloud-native concepts.
• Awareness of AI tools for software engineering (e.g., code assistance, test generation, observability insights).
• Understanding of secure and scalable application design (a plus).

Qualifications

• B.Tech or M.Tech in Computer Science Engineering, AI/ML.
• 70% or 7 CGPA aggregate in the current degree.
• No active backlogs at the time of application.
• Willing to work in GE HealthCare premises during the internship.
• Willing to work on any projects as assigned based on fitment and business need.