We are proud to be consistently recognized as one of the world’s best places to work. We are currently the top ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 spot a record seven times. Extraordinary teams are at the heart of our business strategy, but these don’t happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.
WHO YOU WILL WORK WITH
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.
WHERE YOU’LL FIT WITHIN THE TEAM
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
WHAT YOU’LL DO
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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
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
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 engagement teams
ABOUT YOU
0–2+ years of professional AI / ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributions
Currently pursuing or recently completed a bachelor’s, master’s, or PhD in CS, ML, AI, Data Science, Engineering , or a related quantitative field; or equivalent early-career experience
Strong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributions
Proficiency in Python and some experience building APIs or services ( e.g., REST/gRPC ), or comparable project-based experience
Experience building complex, multi-stack generative AI programs from conception through production
Exposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking ) and familiarity with structured and unstructured data stores
