AI Engineering, Intern (Berlin / Munich)

General Information Job Title AI Engineering, Intern (Berlin / Munich) Job ID 109268 Work Areas Technology & Engineering Employment Type Intern (Full-Time) Location(s) Berlin, Munich Description & Requirements 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 WITHBain’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 TEAMThe 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 DOContribute 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 tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Assist in implementing tool use, function calling, and orchestration across AI workflowsAssist in building agent capabilities including context engineering, memory and state management, orchestration, and tool integrationSupport model experimentation, evaluation design, and production deployment tasks alongside senior team membersWrite clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterateContribute to evaluation and observability for GenAI systems: regression test suites, automated scoring, and prompt or policy iteration loopsGain exposure to responsible AI practices across system design, including:Implementing guardrails, fallbacks, and human-in-the-loop (HITL) workflowsUnderstanding Bain’s Responsible AI standards and supporting alignment in your workContribute to evaluation harnesses and reusable components that scale across client contextsContribute to ML solutions end-to-end, including:Data preparation, feature engineering, model selection, and trainingValidation, testing, and performance analysisApplying appropriate ML methods spanning classical ML and deep learningDeveloping working knowledge of transformer fundamentals and LLM conceptsCollaborate with product, engineering, and data science teammates to build well-structured, reliable AI systemsCommunicate clearly in working sessions, demos, and documentation—with both technical and non-technical audiencesSupport client discussions and documentation as part of broader engagement teamsABOUT YOU0–2+ years of professional AI / ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributionsCurrently 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 experienceStrong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributionsProficiency in Python and some experience building APIs or services (e.g., REST/gRPC), or comparable project-based experienceExperience building complex, multi-stack generative AI programs from conception through productionExposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking) and familiarity with structured and unstructured data storesExposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferredStrong engineering practices: testing, code review, version control, CI/CD, and performance profilingExcellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environmentFluency in English and German is requiredWorking Model & Travel This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office. Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs. Go backGeneral Information Job Title AI Engineering, Intern (Berlin / Munich) Job ID 109268 Work Areas Technology & Engineering Employment Type Intern (Full-Time) Location(s) Berlin, Munich Description & Requirements 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 WITHBain’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 TEAMThe 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 DOContribute 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 tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Assist in implementing tool use, function calling, and orchestration across AI workflowsAssist in building agent capabilities including context engineering, memory and state management, orchestration, and tool integrationSupport model experimentation, evaluation design, and production deployment tasks alongside senior team membersWrite clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterateContribute to evaluation and observability for GenAI systems: regression test suites, automated scoring, and prompt or policy iteration loopsGain exposure to responsible AI practices across system design, including:Implementing guardrails, fallbacks, and human-in-the-loop (HITL) workflowsUnderstanding Bain’s Responsible AI standards and supporting alignment in your workContribute to evaluation harnesses and reusable components that scale across client contextsContribute to ML solutions end-to-end, including:Data preparation, feature engineering, model selection, and trainingValidation, testing, and performance analysisApplying appropriate ML methods spanning classical ML and deep learningDeveloping working knowledge of transformer fundamentals and LLM conceptsCollaborate with product, engineering, and data science teammates to build well-structured, reliable AI systemsCommunicate clearly in working sessions, demos, and documentation—with both technical and non-technical audiencesSupport client discussions and documentation as part of broader engagement teamsABOUT YOU0–2+ years of professional AI / ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributionsCurrently 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 experienceStrong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributionsProficiency in Python and some experience building APIs or services (e.g., REST/gRPC), or comparable project-based experienceExperience building complex, multi-stack generative AI programs from conception through productionExposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking) and familiarity with structured and unstructured data storesExposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferredStrong engineering practices: testing, code review, version control, CI/CD, and performance profilingExcellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environmentFluency in English and German is requiredWorking Model & Travel This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office. Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.General InformationGeneral Information

General Information

Job Title AI Engineering, Intern (Berlin / Munich) Job ID 109268 Work Areas Technology & Engineering Employment Type Intern (Full-Time) Location(s) Berlin, MunichJob Title AI Engineering, Intern (Berlin / Munich) Job ID 109268 Work Areas Technology & Engineering Employment Type Intern (Full-Time) Location(s) Berlin, MunichJob Title AI Engineering, Intern (Berlin / Munich)Job TitleAI Engineering, Intern (Berlin / Munich)Job ID 109268Job ID109268Work Areas Technology & EngineeringWork AreasTechnology & EngineeringEmployment Type Intern (Full-Time)Employment TypeIntern (Full-Time)Location(s) Berlin, MunichLocation(s)Berlin, MunichDescription & RequirementsDescription & Requirements

Description & Requirements

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 WITHBain’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 TEAMThe 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 DOContribute 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 tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Assist in implementing tool use, function calling, and orchestration across AI workflowsAssist in building agent capabilities including context engineering, memory and state management, orchestration, and tool integrationSupport model experimentation, evaluation design, and production deployment tasks alongside senior team membersWrite clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterateContribute to evaluation and observability for GenAI systems: regression test suites, automated scoring, and prompt or policy iteration loopsGain exposure to responsible AI practices across system design, including:Implementing guardrails, fallbacks, and human-in-the-loop (HITL) workflowsUnderstanding Bain’s Responsible AI standards and supporting alignment in your workContribute to evaluation harnesses and reusable components that scale across client contextsContribute to ML solutions end-to-end, including:Data preparation, feature engineering, model selection, and trainingValidation, testing, and performance analysisApplying appropriate ML methods spanning classical ML and deep learningDeveloping working knowledge of transformer fundamentals and LLM conceptsCollaborate with product, engineering, and data science teammates to build well-structured, reliable AI systemsCommunicate clearly in working sessions, demos, and documentation—with both technical and non-technical audiencesSupport client discussions and documentation as part of broader engagement teamsABOUT YOU0–2+ years of professional AI / ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributionsCurrently 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 experienceStrong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributionsProficiency in Python and some experience building APIs or services (e.g., REST/gRPC), or comparable project-based experienceExperience building complex, multi-stack generative AI programs from conception through productionExposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking) and familiarity with structured and unstructured data storesExposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferredStrong engineering practices: testing, code review, version control, CI/CD, and performance profilingExcellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environmentFluency in English and German is requiredWorking Model & Travel This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office. Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.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 WITHBain’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 TEAMThe 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 DOContribute 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 tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Assist in implementing tool use, function calling, and orchestration across AI workflowsAssist in building agent capabilities including context engineering, memory and state management, orchestration, and tool integrationSupport model experimentation, evaluation design, and production deployment tasks alongside senior team membersWrite clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterateContribute to evaluation and observability for GenAI systems: regression test suites, automated scoring, and prompt or policy iteration loopsGain exposure to responsible AI practices across system design, including:Implementing guardrails, fallbacks, and human-in-the-loop (HITL) workflowsUnderstanding Bain’s Responsible AI standards and supporting alignment in your workContribute to evaluation harnesses and reusable components that scale across client contextsContribute to ML solutions end-to-end, including:Data preparation, feature engineering, model selection, and trainingValidation, testing, and performance analysisApplying appropriate ML methods spanning classical ML and deep learningDeveloping working knowledge of transformer fundamentals and LLM conceptsCollaborate with product, engineering, and data science teammates to build well-structured, reliable AI systemsCommunicate clearly in working sessions, demos, and documentation—with both technical and non-technical audiencesSupport client discussions and documentation as part of broader engagement teamsABOUT YOU0–2+ years of professional AI / ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributionsCurrently 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 experienceStrong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributionsProficiency in Python and some experience building APIs or services (e.g., REST/gRPC), or comparable project-based experienceExperience building complex, multi-stack generative AI programs from conception through productionExposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking) and familiarity with structured and unstructured data storesExposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferredStrong engineering practices: testing, code review, version control, CI/CD, and performance profilingExcellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environmentFluency in English and German is requiredWorking Model & Travel This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office. Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.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 WITHBain’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 TEAMThe 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 DOContribute 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 tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Assist in implementing tool use, function calling, and orchestration across AI workflowsAssist in building agent capabilities including context engineering, memory and state management, orchestration, and tool integrationSupport model experimentation, evaluation design, and production deployment tasks alongside senior team membersWrite clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterateContribute to evaluation and observability for GenAI systems: regression test suites, automated scoring, and prompt or policy iteration loopsGain exposure to responsible AI practices across system design, including:Implementing guardrails, fallbacks, and human-in-the-loop (HITL) workflowsUnderstanding Bain’s Responsible AI standards and supporting alignment in your workContribute to evaluation harnesses and reusable components that scale across client contextsContribute to ML solutions end-to-end, including:Data preparation, feature engineering, model selection, and trainingValidation, testing, and performance analysisApplying appropriate ML methods spanning classical ML and deep learningDeveloping working knowledge of transformer fundamentals and LLM conceptsCollaborate with product, engineering, and data science teammates to build well-structured, reliable AI systemsCommunicate clearly in working sessions, demos, and documentation—with both technical and non-technical audiencesSupport client discussions and documentation as part of broader engagement teamsABOUT YOU0–2+ years of professional AI / ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributionsCurrently 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 experienceStrong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributionsProficiency in Python and some experience building APIs or services (e.g., REST/gRPC), or comparable project-based experienceExperience building complex, multi-stack generative AI programs from conception through productionExposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking) and familiarity with structured and unstructured data storesExposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferredStrong engineering practices: testing, code review, version control, CI/CD, and performance profilingExcellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environmentFluency in English and German is requiredWorking Model & Travel This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office. Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.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 WITHBain’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 TEAMThe 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 DOContribute 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 tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Assist in implementing tool use, function calling, and orchestration across AI workflowsAssist in building agent capabilities including context engineering, memory and state management, orchestration, and tool integrationSupport model experimentation, evaluation design, and production deployment tasks alongside senior team membersWrite clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterateContribute to evaluation and observability for GenAI systems: regression test suites, automated scoring, and prompt or policy iteration loopsGain exposure to responsible AI practices across system design, including:Implementing guardrails, fallbacks, and human-in-the-loop (HITL) workflowsUnderstanding Bain’s Responsible AI standards and supporting alignment in your workContribute to evaluation harnesses and reusable components that scale across client contextsContribute to ML solutions end-to-end, including:Data preparation, feature engineering, model selection, and trainingValidation, testing, and performance analysisApplying appropriate ML methods spanning classical ML and deep learningDeveloping working knowledge of transformer fundamentals and LLM conceptsCollaborate with product, engineering, and data science teammates to build well-structured, reliable AI systemsCommunicate clearly in working sessions, demos, and documentation—with both technical and non-technical audiencesSupport client discussions and documentation as part of broader engagement teamsABOUT YOU0–2+ years of professional AI / ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributionsCurrently 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 experienceStrong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributionsProficiency in Python and some experience building APIs or services (e.g., REST/gRPC), or comparable project-based experienceExperience building complex, multi-stack generative AI programs from conception through productionExposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking) and familiarity with structured and unstructured data storesExposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferredStrong engineering practices: testing, code review, version control, CI/CD, and performance profilingExcellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environmentFluency in English and German is requiredWorking Model & Travel This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office. Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.

WHAT MAKES US A GREAT PLACE TO WORK

WHAT MAKES US A GREAT PLACE TO WORKWHAT 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.

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.Glassdoor’s Best Places to Work list

WHO YOU WILL WORK WITH

WHO YOU WILL WORK WITHWHO 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.

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.AI, Insights & Solutions (AIS) team

WHERE YOU’LL FIT WITHIN THE TEAM

WHERE YOU’LL FIT WITHIN THE TEAMWHERE 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.

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.

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

WHAT YOU’LL DOWHAT 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 tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)
• 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) workflowsUnderstanding 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 trainingValidation, testing, and performance analysisApplying appropriate ML methods spanning classical ML and deep learningDeveloping 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

ABOUT YOUABOUT 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

bachelor’s, master’s, or PhD in CS, ML, AI, Data Science, Engineering

• 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

Pythone.g., REST/gRPC

• Experience building complex, multi-stack generative AI programs from conception through production

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

(e.g., vector search, hybrid retrieval, rerankingstructured and unstructured data stores

• Exposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferred

agentic patterns (context management, tool integration, orchestration, memory/state handling)

• Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling

esting, 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 and German is required

EnglishGerman

Working Model & Travel

Working Model & TravelWorking Model & Travel

• This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office.

minimum of three days per week working together in person

• Travel may be required beyond your home office / primary working location. Frequency and destination vary by project needs.