AI Engineering Intern (Summer 2027)

Bain & Company is a consulting firm whose AI, Insights & Solutions team designs and delivers AI-powered solutions for clients. The AI Engineering Intern will contribute to generative AI applications, agentic solutions, machine learning systems, APIs, and production deployments while collaborating with engineers, consultants, and data scientists.

What you'll do:

• 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

What they're looking for:

• • 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
• • Exposure to agentic patterns (context management, tool integration, orchestration, memory/state handling)
• • Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling
• • Excellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environment
• • This role requires in-person collaboration, and you must be based in (or open to working from) New York or San Francisco
• • You'll need to co-locate with your team at least three days a week , whether that's in a Bain office or at a client site, which may require travel
• Hands-on experience preferred

Benefits:

• A 10-week internship with hands-on exposure to the full AI development lifecycle
• Close mentorship from experienced engineers, consultants, and data scientists
• Frequent feedback and increasing responsibility over time
• Significant learning and growth opportunities through Bain’s apprenticeship model
• Opportunities to collaborate with major AI ecosystem partners through Bain’s partnerships
• Successful interns may be considered for full-time offers to begin based on availability / graduation date