AI Engineering, Intern (Madrid)

Bain & Company; Madrid; Presencial; EUR 13.000 - 20.000; A tiempo parcial

Descripción de la vacante

Bain & Company in Madrid is seeking an AI Engineering Intern to contribute to GenAI applications and agentic solutions. You will work with experienced engineers, consultants, and data scientists, gaining hands-on exposure across the AI development lifecycle.

This learning-first role offers mentorship, real project work, and increasing responsibility as you move from prototype to production-ready solutions, collaborating with partners and clients to apply AI in enterprise settings.

Formación

• 0–2 years of professional AI/ML engineering experience (internship/projects accepted).
• Pursuing or completed a bachelor’s, master’s, or PhD in CS/ML/AI/Data Science or related field.
• Proficiency in Python and experience building APIs or services (REST/gRPC).
• Experience building GenAI programs from concept to production.
• Exposure to retrieval and search systems (vector/hybrid) and data stores.

Responsabilidades

• Design and develop GenAI applications (e.g., copilots, workflow automation, decision support) using modern LLM stacks.
• Implement AI pipelines and components: RAG, fine-tuning, embeddings, and hybrid retrieval.
• Assist in tool usage, function calls, and orchestration across AI workflows.
• Assist in building agent capabilities including context engineering, memory/state handling, orchestration, and tool integration.
• Support model experiments, evaluation design, and production deployment tasks with 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 tests, automated scoring, prompt/policy iteration.
• Adhere to responsible AI practices: guardrails, HITL, and alignment with Bain standards.
• Collaborate with product, engineering, and data science teammates to build reliable AI systems.
• Communicate clearly in sessions, demos, and documentation with technical and non-technical audiences.

Conocimientos

Strong communication

English fluency

Client-facing mindset

Team collaboration

Analytical thinking

Educación

Bachelor's/Master's/PhD in CS/ML/AI/Data Science

Herramientas

Python

REST APIs

gRPC

CI/CD

Git

Deployment

LLM tooling

Descripción del empleo

WHAT MAKES US A GREAT PLACE TO WORK

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

Bains 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 Bains 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.

Bains 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 Bains 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 Bains partnerships, contributing to real client deployments and shaping how emerging capabilities are applied in enterprise settings

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 Bains 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 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
• Exposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); 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
• Fluency in English is required

Working Model & Travel

• This role requires a minimum of three days per week working together in person, either at a client location or at your Bains home office.
• Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.