AI PLATFORM ENGINEERING INTERN

About the program EduRankAI is an Artificial Intelligence, Education Technology, Research, and Enterprise Technology organization developing intelligent digital platforms, enterprise software, and technology solutions for academia, industry, government, and global organizations. The AI Platform Engineering Internship provides practical exposure to designing, developing, and maintaining scalable platforms that support the complete lifecycle of artificial intelligence systems. Interns will contribute to building reusable AI infrastructure, developer platforms, workflow orchestration systems, model serving environments, data services, and enterprise AI ecosystems that accelerate the development and deployment of intelligent applications. Working alongside artificial intelligence, software engineering, cloud engineering, DevOps, machine learning, and research teams, interns will gain handson experience in developing AI platforms, backend services, deployment environments, platform automation, resource orchestration, and developer tools while strengthening their understanding of productionscale AI engineering. Key Responsibilities Assist in developing AI platform services and developer infrastructure. Support platform components for model training, deployment, and inference. Build reusable APIs, SDKs, and backend services for AI applications. Assist in platform automation and workflow orchestration. Support model serving infrastructure and deployment pipelines. Participate in platform scalability, reliability, and performance optimization projects. Assist in monitoring AI platform health and operational metrics. Support cloudnative AI platform deployments and distributed services. Prepare technical documentation, architecture diagrams, and engineering reports. Collaborate with AI, software engineering, DevOps, cloud engineering, and research teams on live projects. Stay updated with advancements in AI platform engineering, distributed systems, and cloudnative technologies. Perform additional AI platform engineering assignments as required. Learning Outcomes Interns will gain practical exposure to: AI Platform Engineering Platform Architecture AI Developer Platforms Backend Engineering API Development SDK Development Workflow Orchestration Model Serving Infrastructure Automation Distributed Systems CloudNative Platforms Platform Monitoring Resource Management AI Service Architecture Enterprise AI Platforms Platform Reliability Engineering Technical Documentation Eligibility Students pursuing or having completed: B.E.B.Tech in Computer Science Engineering Artificial Intelligence Machine Learning Data Science Software Engineering Information Technology Cloud Computing Electronics Communication Engineering M.E.M.Tech in relevant disciplines MCA M.Sc. in Computer Science, Artificial Intelligence, Data Science, Information Technology, or related disciplines Any equivalent programme Strong programming skills, software engineering fundamentals, cloud computing concepts, distributed systems knowledge, and an interest in Artificial Intelligence platforms and enterprise software development will be an added advantage but are not mandatory. Department Artificial Intelligence Data Science Qualification Type UG PG Qualification B.E. B.Tech M.E. M.Tech MCA M.Sc. Select Specialisation Computer Science Engineering Artificial Intelligence Machine Learning Data Science Software Engineering Information Technology Cloud Computing Electronics Communication Engineering Mathematics Statistics Any Relevant Engineering or Science Discipline Perks Internship Certificate Letter of Recommendation (Performance Based) Mentorship from experienced AI, cloud, and platform engineering professionals. Opportunity to contribute to live AI platform, infrastructure, and enterprise engineering projects. Exposure to platform architecture, backend engineering, cloud-native technologies, distributed systems, and AI service development. Professional development sessions on Artificial Intelligence, platform engineering, software engineering, cloud computing, and research methodologies. Outstanding performers may be considered for extended internships, leadership opportunities, or future full-time positions based on organizational requirements. Who can apply? Only those candidates can apply who: are from Any and specialisation from are available for duration of 3 Months have relevant skills and interests Terms of Engagement Internship Type: Full-Time Mode of Internship: Online Duration: 3 Months Working Days: 6 Days per Week Total Engagement: Approximately 40 Hours Per Week (?480 Hours over 12 weeks) Project Work / Departmental Responsibilities: Approximately 5 Hours Per Day Holistic Well-being & Personal Development: Approximately 1 Hour 40 Minutes (1.67 Hours) Per Day, including physical fitness, mindfulness, reading, reflective learning, leadership development, community engagement, and other approved personal development activities. Weekly mentor reviews and performance evaluations will be conducted. Interns are expected to maintain professionalism, confidentiality, ethical conduct, and adherence to organizational policies. This is an unpaid internship. Internship Certificate will be awarded upon successful completion of internship requirements. Internship does not constitute an offer of employment. Number of openings 10