Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this AI Engineering Intern (Summer 2027) role.

Rezi rewrites your resume against Bain & Company's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the AI Engineering Intern (Summer 2027) posting at Bain & Company — free, in seconds.

About the Role

Contribute to the design and development of generative AI applications and agentic solutions for Bain’s clients. Gain hands-on exposure to the full AI development lifecycle, from prototyping through production deployment, working alongside experienced engineers, consultants, and data scientists. This is a learning-first role focused on growth through real project work, mentorship, feedback, and increasing responsibility.

Responsibilities

Contribute to the design and development of GenAI applications using modern LLM stacks.
Support the implementation of AI pipelines and components, including Retrieval-Augmented Generation (RAG), fine-tuning, embedding generation, and hybrid retrieval strategies.
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.
Write clean, testable code and contribute to APIs and services through the full SDLC.
Contribute to evaluation and observability for GenAI systems.
Gain exposure to responsible AI practices across system design, including implementing guardrails and human-in-the-loop workflows.
Contribute to evaluation harnesses and reusable components.
Contribute to ML solutions end-to-end, including data preparation, feature engineering, model selection, training, validation, testing, and performance analysis.
Apply appropriate ML methods spanning classical ML and deep learning.
Develop 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.
Support client discussions and documentation as part of broader engagement teams.

Requirements

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, or comparable project-based experience.
Experience building complex, multi-stack generative AI programs from conception through production.
Exposure to retrieval and search systems and familiarity with structured and unstructured data stores.
Exposure to agentic patterns; hands-on experience preferred.
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.

Skills

Python
API development
Generative AI
LLM stacks
Retrieval-Augmented Generation (RAG)
Fine-tuning
Parameter-efficient tuning
Embedding generation
Hybrid retrieval strategies
Vector search
Graph search
Keyword search
Tool use
Function calling
Orchestration
Agentic solutions
Context engineering
Memory management
State management
Model experimentation
Model evaluation
Production deployment
Software Development Lifecycle (SDLC)
Testing
Code review
Version control
CI/CD
Performance profiling
Responsible AI
Guardrails
Human-in-the-loop (HITL)
ML pipelines
Data preparation
Feature engineering
Model selection
Model training
Validation
Performance analysis
Classical ML
Deep learning
Transformer fundamentals
LLM concepts
Interpersonal skills
Communication skills

Location

New York
San Francisco

Work Type

Intern (Full-Time)
In-person collaboration
Hybrid (at least three days a week in office or client site)

Experience Level

0-2+ years of professional AI/ML engineering experience
Intern

Education Level

Bachelor's degree in CS, ML, AI, Data Science, Engineering, or related quantitative field
Master's degree in CS, ML, AI, Data Science, Engineering, or related quantitative field
PhD in CS, ML, AI, Data Science, Engineering, or related quantitative field

About the Company

Proudly recognized as one of the world’s best places to work, ranked #1 consulting firm on Glassdoor’s Best Places to Work list seven times.
Focuses on building extraordinary teams through a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive environment.
Hires exceptional talent and creates an environment where individuals can thrive professionally and personally.
Bain’s AI, Insights & Solutions (AIS) team designs and delivers AI-powered solutions for clients to create measurable business impact.
Operates in multidisciplinary teams with consultants, product experts, designers, architects, engineers, and client stakeholders.
Translates ambiguous business problems into robust AI applications.
Offers significant learning and growth opportunities through an apprenticeship model.
Works with clients on board-level and executive priorities.
Builds the technical core of transformations and helps move solutions from prototype to adoption.
Collaborates with major AI ecosystem partners through Bain’s partnerships.
Contributes to real client deployments and shapes the application of emerging capabilities in enterprise settings.