Senior Manager, AI Engineering

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 Data Science & Machine Learning 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. 

ABOUT BAIN AI, INSIGHTS & SOLUTIONS (AIS)

Bain’s AI, Insights & Solutions team works with clients to design and deliver AI-powered solutions that create measurable business impact. We operate in multidisciplinary teams alongside Bain consultants, experts in product, design, architecture, and engineering, and client stakeholders. Together, we translate ambiguous business problems into robust AI applications that can be piloted, scaled, and adopted.

WHERE YOU’LL FIT WITHIN THE TEAM

As a Senior Manager in our Data Science & Machine Learning Engineering guild, you will lead the design and delivery of advanced machine learning and agentic AI systems across industries. You’ll combine deep hands-on technical expertise with team leadership and client ownership, guiding multidisciplinary teams while staying closely involved in architecture, model development, evaluation strategy, and production deployment.

This role sits at the intersection of classical machine learning, deep learning, generative AI, and emerging agentic systems. You will help translate business ambition into scalable, secure, production-grade AI solutions.

THE 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.

As a Senior Manager, you will shape how machine learning, data science, and agentic AI are architected and deployed in complex enterprise environments, ensuring that solutions move beyond experimentation into sustained, scalable value creation.

WHAT YOU’LL DO

Lead enterprise AI and agentic system design

• Architect and oversee delivery of generative AI and agentic AI applications, from proof of concept and MVP through to scaled production deployment
• Design LLM-driven applications such as copilots, workflow automation tools, and decision-support systems integrated into enterprise environments
• Build robust agentic workflows, including tool use, orchestration, routing, memory and state management, human-in-the-loop controls, and clear failure handling
• Design advanced retrieval and knowledge systems, including hybrid search, vector databases, knowledge graphs, metadata strategy, reranking, caching, and source attribution
• Balance performance, reliability, latency, cost, security, and adoption in real-world enterprise settings

Drive machine learning and data science excellence

• Oversee the full machine learning lifecycle, including data preparation, feature engineering, model selection, training, validation, deployment, and monitoring
• Apply the right methodologies across classical machine learning, deep learning, natural language processing, computer vision, and transformer-based architectures
• Establish reproducible pipelines with strong experiment tracking, versioning, documentation, and validation practices
• Design evaluation and observability frameworks for LLM and agentic systems, including structured evaluations, regression testing, tracing, automated scoring, and iteration loops
• Champion best practices in ML engineering, MLOps, and GenAIOps, including CI/CD, containerization, infrastructure as code, and environment parity

Build scalable assets and frameworks

• Develop reusable machine learning and agentic AI frameworks, accelerators, templates, and evaluation harnesses that can scale across clients
• Transform prototype code into production-grade, optimized software
• Ensure secure enterprise deployment with appropriate access controls, responsible AI guardrails, and strong handling of sensitive data

Lead teams and grow capability

• Lead multidisciplinary machine learning and data science teams during client delivery, setting technical direction, reviewing architecture and code, and ensuring high-quality, scalable outcomes
• Advise and coach machine learning engineers and data scientists on professional development, providing mentorship, performance feedback, and growth guidance within the Data Science & Machine Learning Engineering guild
• Set technical standards and review key architectural decisions
• Support AIS leadership in expanding Bain’s machine learning and AI engineering capabilities
• Build relationships with key ecosystem and technology partners

Operate in a client-facing consulting environment

• Partner with consulting teams and senior business leaders to define AI strategies and delivery roadmaps
• Translate ambiguous business objectives into scalable analytics and engineering solutions
• Communicate complex technical concepts clearly to non-technical audiences
• Contribute to proposal shaping, effort sizing, architecture trade-offs, and risk assessment
• Travel as required, approximately 30%, depending on client needs

ABOUT YOU

• Advanced degree in Computer Science, Engineering, Statistics, Applied Mathematics, Physics, or a related quantitative discipline
• 10+ years of experience in software engineering, analytics development, or machine learning engineering
• 3+ years of experience leading teams of data scientists, machine learning engineers, or AI engineers
• Deep understanding of computer science fundamentals, system design, and the full machine learning and agentic AI lifecycle
• Strong expertise in Python and major machine learning frameworks such as Scikit-learn, TensorFlow, Keras, and PyTorch
• Deep expertise in neural networks and deep learning, including practical applications in natural language processing, computer vision, reinforcement learning, and transformer-based architectures
• Experience with agentic frameworks such as LangGraph, CrewAI, OpenAI Agents, DSPy, or similar tools
• Experience designing evaluation and observability systems for LLM and agent-based workflows, such as OpenAI Evals, LangSmith, Arize Phoenix, or Guardrails AI
• Strong MLOps experience, including MLflow, Kubeflow, CI/CD, Docker, Kubernetes, and Terraform
• Proficiency in at least one major cloud platform, including AWS, GCP, or Azure, and associated machine learning services
• Experience with distributed computing frameworks such as Spark, Ray, or Dask, and modern data pipelines
• Strong communication skills and the ability to influence both technical and non-technical stakeholders
• Fluency in English and Portuguese; Spanish is a plus