GenAI Engineer Intern: Build Enterprise AI Solutions

Bain & Company; San Francisco (CA); On-site; USD 30,000 - 45,000; Full time

Benefits offered by this job

Mentorship program

Hands-on project work

Job summary

Bain & Company is offering a 10-week internship with the AIS team to design and develop generative AI applications and agentic solutions for clients. You will work alongside engineers, consultants, and data scientists, gaining hands-on exposure from prototyping to production deployment in a learning-first environment.

You will grow through real project work, frequent feedback, and increasing responsibility.

Qualifications

• Pursuing or recently completed bachelor’s, master’s, or PhD in CS/ML/AI or related field.
• Strong academic performance or demonstrated excellence through projects, internships, or open-source work.
• Proficiency in Python and experience building APIs or services (REST/gRPC).
• Experience building complex, multi-stack GenAI programs from conception to production.
• Exposure to retrieval/search systems and familiarity with data stores.

Responsibilities

• Contribute to the design and development of GenAI applications (copilots, automation, decision support).
• Assist in implementing AI pipelines, including RAG, fine-tuning, embedding optimization, and hybrid retrieval.
• Collaborate to build agent capabilities: context management, memory state, orchestration, tool integration.
• Support model experimentation, evaluation design, and production deployment tasks with senior team members.
• Write clean, testable code and contribute to APIs/services through the full SDLC.

Skills

Python

APIs

CI/CD

Version control

ML engineering

Education

Bachelor's or Master's in CS/ML/AI

Tools

Transformers

LLMs

Vector databases

RAG

Job description

Bain & Company is offering a 10-week internship with the AIS team to design and develop generative AI applications and agentic solutions for clients. You will work alongside engineers, consultants, and data scientists, gaining hands-on exposure from prototyping to production deployment in a learning-first environment.

You will grow through real project work, frequent feedback, and increasing responsibility.