AI Engineering, Intern; Dubai

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Bain's AI, Insights & Solutions (AIS) team works with clients to design and deliver AI-powered solutions that create measurable business impact. You'll operate in multidisciplinary teams alongside Bain consultants, other experts in product, design, architecture, and engineering, and client stakeholders, translating ambiguous business problems into robust AI applications that can be piloted, scaled, and adopted.

The AI Engineering Intern will contribute to the design and development of generative AI applications and agentic solutions for Bain's clients. Working alongside experienced engineers, consultants, and data scientists, you will gain hands‑on exposure to the full AI development lifecycle—from early prototyping through to production‑ready deployment. This is a learning‑first role: you will grow through real project work, close mentorship, frequent feedback, and increasing responsibility over time.

Bain offers significant learning and growth opportunities through our apprenticeship model. You will learn by doing, with support from experienced teammates, frequent feedback, and increasing responsibility over time Bain works with clients on board‑level and executive priorities. As an intern, you will build the technical core of transformations and help move solutions from prototype to real adoption. You will have opportunities to collaborate with major AI ecosystem partners through Bain's partnerships, contributing to real client deployments and shaping how emerging capabilities are applied in enterprise settings

• Contribute to the design and development of GenAI applications (e.g., copilots, workflow automation, decision support) using modern LLM stacks.
• Support the implementation of AI pipelines and components, including:
  • Retrieval-Augmented Generation (RAG)
  • Fine-tuning and parameter‑efficient tuning
  • Embedding generation and optimization
  • Hybrid retrieval strategies (vector, graph, keyword)
• Assist in implementing tool use, function calling, and orchestration across AI workflows
• Assist in building agent capabilities including context engineering, memory and state management, orchestration, and tool integration
• Support model experimentation, evaluation design, and production deployment tasks alongside senior team members
• Write clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterate
• Contribute to evaluation and observability for GenAI systems: regression test suites, automated scoring, and prompt or policy iteration loops
• Gain exposure to responsible AI practices across system design, including:
  • Implementing guardrails, fallbacks, and human‑in‑the‑loop (HITL) workflows
  • Understanding Bain's Responsible AI standards and supporting alignment in your work
• Contribute to evaluation harnesses and reusable components that scale across client contexts
• Contribute to ML solutions end‑to‑end, including:
  • Data preparation, feature engineering, model selection, and training
  • Validation, testing, and performance analysis
  • Applying appropriate ML methods spanning classical ML and deep learning
  • Developing working knowledge of transformer fundamentals and LLM concepts
• Collaborate with product, engineering, and data science teammates to build well‑structured, reliable AI systems
• Communicate clearly in working sessions, demos, and documentation- with both technical and non‑technical audiences
• Support client discussions and documentation as part of broader…