Expert Senior Manager, AI Engineering

General Information Job Title Expert Senior Manager, AI Engineering Job ID 106099 Work Areas Technology & Engineering Employment Type Permanent 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 overall 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. About Bain AI, Insights & Solutions (AIS)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. The Impact You’ll HaveBain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization. As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries. The Role The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders. You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings. Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time. What You’ll Do Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Integrate reasoning, tool use, function calling, and orchestration across complex workflowsEngineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystemsLead everything from early-stage research, model experimentation, and evaluation design to production system deploymentOversee API development, microservices, CI/CD pipelines, observability, and cloud-native deploymentBuild scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsAct as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmapsMentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety What We’re Looking For8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilitiesGerman languate proficience at C1 level or higherDemonstrated experience leading complex, multi-stack generative AI programs from conception through productionStrong executive communication skills with the ability to translate highly technical concepts to business stakeholdersTrack record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groupsAdvanced prompt engineering, context engineering, and conversation designStrong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM appsDeep experience with:Advanced RAG architectures (vector, hybrid, graph-based retrieval)Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentDeep familiarity with cost optimization and computational tradeoffs for LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsClear ability to lead, mentor, and inspire technical teamsExperience in client-facing consulting or enterprise transformation environments is a strong plus Working Model & TravelThis 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 is required beyond your home office / primary working location. Frequency and destination vary by project needs. Go backGeneral Information Job Title Expert Senior Manager, AI Engineering Job ID 106099 Work Areas Technology & Engineering Employment Type Permanent 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 overall 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. About Bain AI, Insights & Solutions (AIS)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. The Impact You’ll HaveBain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization. As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries. The Role The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders. You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings. Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time. What You’ll Do Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Integrate reasoning, tool use, function calling, and orchestration across complex workflowsEngineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystemsLead everything from early-stage research, model experimentation, and evaluation design to production system deploymentOversee API development, microservices, CI/CD pipelines, observability, and cloud-native deploymentBuild scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsAct as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmapsMentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety What We’re Looking For8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilitiesGerman languate proficience at C1 level or higherDemonstrated experience leading complex, multi-stack generative AI programs from conception through productionStrong executive communication skills with the ability to translate highly technical concepts to business stakeholdersTrack record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groupsAdvanced prompt engineering, context engineering, and conversation designStrong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM appsDeep experience with:Advanced RAG architectures (vector, hybrid, graph-based retrieval)Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentDeep familiarity with cost optimization and computational tradeoffs for LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsClear ability to lead, mentor, and inspire technical teamsExperience in client-facing consulting or enterprise transformation environments is a strong plus Working Model & TravelThis 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 is required beyond your home office / primary working location. Frequency and destination vary by project needs.General InformationGeneral Information

General Information

Job Title Expert Senior Manager, AI Engineering Job ID 106099 Work Areas Technology & Engineering Employment Type Permanent Full-Time Location(s) Berlin, MunichJob Title Expert Senior Manager, AI Engineering Job ID 106099 Work Areas Technology & Engineering Employment Type Permanent Full-Time Location(s) Berlin, MunichJob Title Expert Senior Manager, AI EngineeringJob TitleExpert Senior Manager, AI EngineeringJob ID 106099Job ID106099Work Areas Technology & EngineeringWork AreasTechnology & EngineeringEmployment Type Permanent Full-TimeEmployment TypePermanent Full-TimeLocation(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 overall 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. About Bain AI, Insights & Solutions (AIS)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. The Impact You’ll HaveBain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization. As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries. The Role The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders. You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings. Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time. What You’ll Do Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Integrate reasoning, tool use, function calling, and orchestration across complex workflowsEngineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystemsLead everything from early-stage research, model experimentation, and evaluation design to production system deploymentOversee API development, microservices, CI/CD pipelines, observability, and cloud-native deploymentBuild scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsAct as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmapsMentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety What We’re Looking For8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilitiesGerman languate proficience at C1 level or higherDemonstrated experience leading complex, multi-stack generative AI programs from conception through productionStrong executive communication skills with the ability to translate highly technical concepts to business stakeholdersTrack record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groupsAdvanced prompt engineering, context engineering, and conversation designStrong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM appsDeep experience with:Advanced RAG architectures (vector, hybrid, graph-based retrieval)Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentDeep familiarity with cost optimization and computational tradeoffs for LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsClear ability to lead, mentor, and inspire technical teamsExperience in client-facing consulting or enterprise transformation environments is a strong plus Working Model & TravelThis 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 is 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 overall 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. About Bain AI, Insights & Solutions (AIS)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. The Impact You’ll HaveBain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization. As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries. The Role The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders. You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings. Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time. What You’ll Do Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Integrate reasoning, tool use, function calling, and orchestration across complex workflowsEngineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystemsLead everything from early-stage research, model experimentation, and evaluation design to production system deploymentOversee API development, microservices, CI/CD pipelines, observability, and cloud-native deploymentBuild scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsAct as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmapsMentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety What We’re Looking For8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilitiesGerman languate proficience at C1 level or higherDemonstrated experience leading complex, multi-stack generative AI programs from conception through productionStrong executive communication skills with the ability to translate highly technical concepts to business stakeholdersTrack record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groupsAdvanced prompt engineering, context engineering, and conversation designStrong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM appsDeep experience with:Advanced RAG architectures (vector, hybrid, graph-based retrieval)Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentDeep familiarity with cost optimization and computational tradeoffs for LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsClear ability to lead, mentor, and inspire technical teamsExperience in client-facing consulting or enterprise transformation environments is a strong plus Working Model & TravelThis 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 is 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 overall 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. About Bain AI, Insights & Solutions (AIS)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. The Impact You’ll HaveBain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization. As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries. The Role The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders. You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings. Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time. What You’ll Do Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Integrate reasoning, tool use, function calling, and orchestration across complex workflowsEngineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystemsLead everything from early-stage research, model experimentation, and evaluation design to production system deploymentOversee API development, microservices, CI/CD pipelines, observability, and cloud-native deploymentBuild scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsAct as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmapsMentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety What We’re Looking For8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilitiesGerman languate proficience at C1 level or higherDemonstrated experience leading complex, multi-stack generative AI programs from conception through productionStrong executive communication skills with the ability to translate highly technical concepts to business stakeholdersTrack record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groupsAdvanced prompt engineering, context engineering, and conversation designStrong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM appsDeep experience with:Advanced RAG architectures (vector, hybrid, graph-based retrieval)Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentDeep familiarity with cost optimization and computational tradeoffs for LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsClear ability to lead, mentor, and inspire technical teamsExperience in client-facing consulting or enterprise transformation environments is a strong plus Working Model & TravelThis 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 is 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 overall 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. About Bain AI, Insights & Solutions (AIS)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. The Impact You’ll HaveBain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization. As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries. The Role The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders. You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings. Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time. What You’ll Do Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Integrate reasoning, tool use, function calling, and orchestration across complex workflowsEngineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystemsLead everything from early-stage research, model experimentation, and evaluation design to production system deploymentOversee API development, microservices, CI/CD pipelines, observability, and cloud-native deploymentBuild scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsAct as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmapsMentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety What We’re Looking For8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilitiesGerman languate proficience at C1 level or higherDemonstrated experience leading complex, multi-stack generative AI programs from conception through productionStrong executive communication skills with the ability to translate highly technical concepts to business stakeholdersTrack record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groupsAdvanced prompt engineering, context engineering, and conversation designStrong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM appsDeep experience with:Advanced RAG architectures (vector, hybrid, graph-based retrieval)Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentDeep familiarity with cost optimization and computational tradeoffs for LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsClear ability to lead, mentor, and inspire technical teamsExperience in client-facing consulting or enterprise transformation environments is a strong plus Working Model & TravelThis 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 is 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 overall 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 onGlassdoor’s Best Places to Work listGlassdoor’s Best Places to Work listand have earned the #1 overall 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.

About Bain AI, Insights & Solutions (AIS)

About Bain AI, Insights & Solutions (AIS)About Bain AI, Insights & Solutions (AIS)

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’sAI, Insights & Solutions (AIS) teamAI, Insights & Solutions (AIS) teamworks 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.

The Impact You’ll Have

The Impact You’ll HaveThe Impact You’ll Have

Bain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization.

Bain works with clients on board-level and executive priorities, helping deliver step-change results across growth, productivity, and resilience. In that context, AI is rarely a point solution. The most meaningful outcomes come from building AI as part of an integrated system that combines technology with redesigned processes, operating model changes, and adoption at scale across the organization.

As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries.

As an AI Engineering leader in AIS, you will support the building of the technical core within these transformations and work as part of broader Bain consulting teams to move solutions from prototype to real adoption. The result is measurable impact at the company or enterprise level and, in many cases, helps clients set new performance standards for their industries.

The Role

The RoleThe Role

The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders.

The Expert Senior Manager / Associate Partner AI Engineer will architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients. As a leader in the practice, you will sit at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You will own the full lifecycle — from research and experimentation to production deployment and ongoing optimization — and guide teams across engineering, product, data science, ethics, and client stakeholders.

You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings.

You will have opportunities to work with major AI ecosystem partners through Bain’s partnerships, collaborating on real client deployments and helping shape how emerging capabilities are applied in enterprise settings.

Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time.

Bain offers significant learning and growth opportunities through the breadth and depth of problems we solve, the level of impact we help clients achieve, and our apprenticeship model. You will learn while doing, with support from other experienced teammates, frequent feedback, and increasing responsibility over time.

What You’ll Do

What You’ll DoWhat You’ll DoDesign, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)Integrate reasoning, tool use, function calling, and orchestration across complex workflowsEngineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystemsLead everything from early-stage research, model experimentation, and evaluation design to production system deploymentOversee API development, microservices, CI/CD pipelines, observability, and cloud-native deploymentBuild scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvementBalance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standardsBuild automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updatesDesign and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiencyPartner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systemsAct as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmapsMentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety

• Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.

Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications.

• Architect multi-component pipelines, including:Retrieval-Augmented Generation (RAG)Fine-tuning and parameter-efficient tuningEmbedding generation and optimizationHybrid retrieval strategies (vector, graph, keyword)

Architect multi-component pipelines, including:

• Retrieval-Augmented Generation (RAG)

Retrieval-Augmented Generation (RAG)

• Fine-tuning and parameter-efficient tuning

Fine-tuning and parameter-efficient tuning

• Embedding generation and optimization

Embedding generation and optimization

• Hybrid retrieval strategies (vector, graph, keyword)

Hybrid retrieval strategies (vector, graph, keyword)

• Integrate reasoning, tool use, function calling, and orchestration across complex workflows

Integrate reasoning, tool use, function calling, and orchestration across complex workflows

• Engineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystems

Engineer advanced agentic systems, ensuring clear separation of concerns, robust memory architecture, and scalable tool ecosystems

• Lead everything from early-stage research, model experimentation, and evaluation design to production system deployment

Lead everything from early-stage research, model experimentation, and evaluation design to production system deployment

• Oversee API development, microservices, CI/CD pipelines, observability, and cloud-native deployment

Oversee API development, microservices, CI/CD pipelines, observability, and cloud-native deployment

• Build scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvement

Build scalable GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvement

• Balance performance, safety, responsible AI principles, and cost across system design:Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflowsPartner with global ethics teams to ensure alignment with Bain’s Responsible AI standards

Balance performance, safety, responsible AI principles, and cost across system design:

• Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflows

Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop (HITL) workflows

• Partner with global ethics teams to ensure alignment with Bain’s Responsible AI standards

Partner with global ethics teams to ensure alignment with Bain’s Responsible AI standards

• Build automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updates

Build automated evaluation suites integrating user signals, continual learning cycles, and ongoing model updates

• Design and implement evaluation frameworks covering:Hallucination rate and factual consistencyRelevance and precision/recallLatency, throughput, and system-level performanceCost tracking and efficiency

Design and implement evaluation frameworks covering:

• Hallucination rate and factual consistency

Hallucination rate and factual consistency

• Relevance and precision/recall

Relevance and precision/recall

• Latency, throughput, and system-level performance

Latency, throughput, and system-level performance

• Cost tracking and efficiency

Cost tracking and efficiency

• Partner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systems

Partner closely with product, engineering, data science, ethics, and infrastructure teams to build robust, compliant AI systems

• Act as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmaps

Act as a thought partner to executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmaps

• Mentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety

Mentor and upskill technical teams on best practices including RAG, agents, prompt engineering, and AI safety

What We’re Looking For

What We’re Looking ForWhat We’re Looking For8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilitiesGerman languate proficience at C1 level or higherDemonstrated experience leading complex, multi-stack generative AI programs from conception through productionStrong executive communication skills with the ability to translate highly technical concepts to business stakeholdersTrack record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groupsAdvanced prompt engineering, context engineering, and conversation designStrong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM appsDeep experience with:Advanced RAG architectures (vector, hybrid, graph-based retrieval)Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)ReAct, RLAIF, and other HITL + feedback loops.AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystemsStrong background in system design, architecture, and production-grade deploymentDeep familiarity with cost optimization and computational tradeoffs for LLM workloadsComfort operating in high-ambiguity environments with collaborative cross-functional teamsClear ability to lead, mentor, and inspire technical teamsExperience in client-facing consulting or enterprise transformation environments is a strong plus

• 8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilities

8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands-on building responsibilities

• German languate proficience at C1 level or higher

German languate proficience at C1 level or higher

• Demonstrated experience leading complex, multi-stack generative AI programs from conception through production

Demonstrated experience leading complex, multi-stack generative AI programs from conception through production

• Strong executive communication skills with the ability to translate highly technical concepts to business stakeholders

Strong executive communication skills with the ability to translate highly technical concepts to business stakeholders

• Track record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groups

Track record of leading engineering teams, mentoring technical talent, and collaborating with diverse cross-functional groups

• Advanced prompt engineering, context engineering, and conversation design

Advanced prompt engineering, context engineering, and conversation design

• Strong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM apps

Strong expertise in evaluation design, experimentation frameworks, and data labeling strategies for LLM apps

• Deep experience with:

Deep experience with:

• Advanced RAG architectures (vector, hybrid, graph-based retrieval)

Advanced RAG architectures (vector, hybrid, graph-based retrieval)

• Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)

Agentic architectures (multi-agent systems, tool selection, routing, memory, planning, reflection)

• ReAct, RLAIF, and other HITL + feedback loops.

ReAct, RLAIF, and other HITL + feedback loops.

• AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystems

AI-Specific Tools & Frameworks - Orchestration frameworks, Vector and graph databases and Model + API ecosystems

• Strong background in system design, architecture, and production-grade deployment

Strong background in system design, architecture, and production-grade deployment

• Deep familiarity with cost optimization and computational tradeoffs for LLM workloads

Deep familiarity with cost optimization and computational tradeoffs for LLM workloads

• Comfort operating in high-ambiguity environments with collaborative cross-functional teams

Comfort operating in high-ambiguity environments with collaborative cross-functional teams

• Clear ability to lead, mentor, and inspire technical teams

Clear ability to lead, mentor, and inspire technical teams

• Experience in client-facing consulting or enterprise transformation environments is a strong plus

Experience in client-facing consulting or enterprise transformation environments is a strong plus

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.

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 is required beyond your home office / primary working location. Frequency and destination vary by project needs.

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