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.
WHO YOU’LL WORK WITH
You’ll join our engineering experts within the AI, Insights & Solutions team. This team is part of Bain’s digital capabilities practice, which includes experts in analytics, engineering, product management, and design. In this multidisciplinary environment, you’ll leverage deep technical expertise with business acumen to help clients tackle their most transformative challenges. You’ll work on integrated teams alongside our general consultants and clients to develop data-driven strategies and innovative solutions. Together, we create human-centric solutions that harness the power of data and artificial intelligence to drive competitive advantage for our clients. Our collaborative and supportive work environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.
WHERE YOU’LL FIT WITHIN THE TEAM
As an Expert Senior Manager, AI Engineer, you’ll architect, build, and scale next-generation generative AI systems and agentic solutions for Bain’s clients.
You’ll work at the intersection of advanced engineering, applied AI research, product strategy, and responsible AI governance. You’ll lead the full lifecycle of AI solutions, from research and experimentation through production deployment and ongoing optimization, while guiding teams across engineering, product, data science, ethics, infrastructure, and client stakeholders.
WHAT YOU’LL DO
In this role, you will:
- Design, build, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade AI applications
- Architect multi-component pipelines across Retrieval-Augmented Generation, fine-tuning, embedding generation, and hybrid retrieval strategies
- Integrate reasoning, tool use, function calling, and orchestration across complex AI workflows
- Engineer advanced agentic systems with robust memory architecture, scalable tool ecosystems, and clear separation of concerns
- Lead work from early-stage research, model experimentation, and evaluation design through production deployment
- Oversee API development, microservices, CI/CD pipelines, observability, and cloud-native deployment
- Build GenAIOps processes for automated testing, regression evaluation, latency monitoring, and continual improvement
- Design evaluation frameworks covering factual consistency, relevance, precision and recall, latency, throughput, cost, and system performance
- Implement guardrails, fallbacks, red-teaming strategies, and human-in-the-loop workflows
- Partner with global ethics teams to align solutions with Bain’s Responsible AI standards
- Advise executives and clients on AI strategy, architecture decisions, emerging capabilities, and implementation roadmaps
- Mentor and upskill technical teams on RAG, agents, prompt engineering, and AI safety
ABOUT YOU
You bring:
- 8-12+ years of experience in software engineering, machine learning engineering, applied AI, or related technical roles
- Significant hands-on experience building and deploying complex AI or machine learning systems
- Demonstrated experience leading multi-stack generative AI programs from concept through production
- Deep expertise in advanced RAG architectures, including vector, hybrid, and graph-based retrieval
- Experience with agentic architectures, including multi-agent systems, tool selection, routing, memory, planning, and reflection
- Strong knowledge of prompt engineering, context engineering, conversation design, and LLM application evaluation
- Experience with orchestration frameworks, vector and graph databases, and model and API ecosystems
- Strong background in system design, architecture, and production-grade deployment
- Familiarity with cost optimization and computational tradeoffs for LLM workloads
- Experience leading engineering teams, mentoring technical talent, and working across cross-functional groups
- Strong executive communication skills, with the ability to translate technical concepts into business implications
- Comfort working in high-ambiguity environments with clients and cross-functional teams
- Fluent in English; Spanish OR Portuguese are mandatory.
Experience in client-facing consulting or enterprise transformation environments is a strong plus.
