AI Product Engineering Intern – Full Stack, DevOps & MLOps

AI Product Engineering InternFull Stack | AI-Assisted Development | DevOps | MLOpsAbout the InternshipVEGAH is looking for motivated AI Product Engineering Interns interested in building, deploying and operating modern AI-powered software products.This is a hands-on engineering internship combining full-stack development, AI-assisted (vibe) coding, DevOps, MLOps and cloud technologies.The intern will collaborate with our engineering team to turn product ideas into functional applications, integrating frontend interfaces, backend APIs, databases, AI/ML capabilities and automated cloud deployment pipelines.We are particularly interested in candidates who can use modern AI coding assistants to accelerate development while understanding the underlying application architecture, code quality, security and deployment requirements.Responsibilities1. Full-Stack Development & AI-Assisted CodingBuild and enhance web applications using React, Next.js, JavaScript/TypeScript, Python and backend frameworks.Use AI-assisted coding tools such as GitHub Copilot, Cursor and Claude Code to rapidly prototype and develop applications.Understand frontend-to-backend integration, REST APIs, authentication, databases and application architecture.Review, debug, test and improve AI-generated code rather than relying on generated output without validation.Translate product requirements into working features and reusable components.2. DevOps & Cloud EngineeringWork with GitHub repositories, branching strategies, pull requests and automated CI/CD pipelines.Support containerization using Docker and deployment to Azure or AWS.Help automate application builds, testing, releases and deployments using GitHub Actions.Learn cloud infrastructure, environment configuration, secrets management and secure authentication.Support application monitoring, logging, health checks and deployment troubleshooting.Explore Infrastructure as Code and automated cloud resource provisioning.3. MLOps & AI IntegrationIntegrate predictive ML models and LLM-based capabilities into applications through APIs.Explore experiment tracking, model versioning and deployment using tools such as MLflow.Support reproducible model training, evaluation and deployment workflows.Work with model serving, inference APIs, monitoring and retraining automation.Explore RAG, AI agents, prompt engineering and LLM API integrations where relevant.4. Product Engineering & AutomationParticipate in end-to-end product development from prototype to deployed application.Work with frontend, backend, databases, APIs and cloud services as part of a unified architecture.Build reusable components, scripts and automation workflows.Help identify performance, reliability, security and cost optimization opportunities.Collaborate with developers and architects to troubleshoot and improve existing products.Required QualificationsWorking knowledge of at least one programming language such as Python, JavaScript or TypeScript.Basic understanding of frontend and backend application development.Familiarity with Git/GitHub and software development fundamentals.Understanding of REST APIs, databases and application integration.Interest in DevOps, cloud engineering, automation and AI-enabled software development.Ability to learn new tools, troubleshoot problems and independently develop working prototypes.Preferred QualificationsExperience with one or more of the following is helpful but not required:Frontend: React, Next.js, HTML, CSS, Tailwind CSS.Backend: Python, FastAPI, Node.js, Express.Databases: PostgreSQL, SQL Server, MongoDB.AI Coding: Cursor, GitHub Copilot, Claude Code, or similar tools.DevOps: GitHub Actions, Docker, CI/CD, Infrastructure as Code.Cloud: Microsoft Azure, AWS, Azure Container Apps, Azure Container Registry.MLOps: MLflow, model serving, experiment tracking, deployment automation.AI/ML: OpenAI APIs, Gemini, Claude, scikit-learn, RAG and AI agents.Students and recent graduates in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Cloud Computing or related disciplines are encouraged to apply.Prior SAP experience is not required.What You Will Work OnYour initial assignments will involve contributing to VEGAH's AI-enabled product development initiatives.Depending on project needs, you may help build application features, integrate AI services, create frontend and backend components, automate CI/CD pipelines, containerize applications, deploy services to the cloud and establish basic operational monitoring.Our goal is to help interns gain practical experience across the complete product engineering lifecycle—from idea and AI-assisted development through testing, deployment, monitoring and continuous improvement.Strong performers may be considered for future opportunities with VEGAH based on business needs and performance.