IBM internship AI Engineer

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. About the role: The internship program is offered for a fixed period of 3 months, with the possibility of extending the collaboration based on performance and business needs. • Assist in designing, developing, and maintaining AI‑powered applications using Python • Support the creation and deployment of MCP servers that expose internal tools, data sources, and workflows to AI copilots • Help integrate AI copilots (such as development copilots or enterprise assistants) with internal systems through MCP • Contribute to defining and managing context schemas, tool interfaces, and prompt‑orchestration workflows • Help build APIs and services that enable secure and scalable AI interactions • Collaborate with product, data, and engineering teams to embed AI features into internal workflows • Assist in performance tuning, reliability improvements, and security checks for AI systems • Stay informed about emerging AI tooling standards, agent frameworks, and Copilot ecosystem developments • Fundamental programming experience in Python • Basic understanding of backend development concepts (e.g., FastAPI, Flask) • Interest in or exposure to the Model Context Protocol (MCP), including: – Building or experimenting with MCP servers – Defining tools or resources – Working with structured context • Interest in AI copilots or AI assistant technologies • Basic knowledge of large language models (LLMs) and prompt engineering principles • Familiarity with REST APIs, JSON‑RPC, or event‑driven architecture concepts • Exposure to cloud platforms such as AWS, Azure, or GCP • Strong analytical, debugging, and problem‑solving abilities • Experience with agent frameworks (such as LangChain or Semantic Kernel) • Exposure to vector databases (Pinecone, Weaviate, FAISS) • Interest in or experience with RAG (Retrieval‑Augmented Generation) systems • Familiarity with authentication or authorization concepts (OAuth, RBAC), especially in AI systems • Exposure to DevOps tooling (Docker, CI/CD) Romania Data & Analytics Hybrid Internship Bucharest, RO