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.
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 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 Manager, AI Engineering in AIS, you will lead the technical delivery of these transformations, bridging individual contribution and team leadership to move solutions from prototype to real adoption. You will take ownership of workstreams, guide more junior engineers, and interface with cross-functional partners and client stakeholders to ensure technical work lands with measurable enterprise impact.
The Role
The Manager, AI Engineering will design, build, and ship generative AI systems and agentic solutions for Bain's clients — while beginning to lead others in doing the same. This role sits at the inflection point between senior individual contributor and emerging technical leader. You will take full ownership of components and workstreams within larger programs, influence technical direction, and actively develop the engineers around you.
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 by doing, with support from experienced teammates, frequent feedback, and increasing responsibility over time.
What You'll Do
Own the design, development, and deployment of generative AI systems and multi-agent workflows within client engagements, taking end-to-end accountability for assigned workstreams.
Architect and build multi-component AI pipelines, including:
Retrieval-Augmented Generation (RAG)
Fine-tuning and parameter-efficient tuning
Embedding generation and optimization
Hybrid retrieval strategies (vector, graph, keyword)
Implement and integrate reasoning, tool use, function calling, and orchestration across AI workflows.
Build and lead delivery of agentic systems with clear separation of concerns, robust memory architecture, and scalable tool integration.
Drive workstreams from research and experimentation through production deployment, maintaining quality and pace.
Build and maintain APIs, microservices, CI/CD pipelines, and cloud-native deployments with strong attention to observability and reliability.
Establish and improve 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) workflows
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
Design and implement evaluation frameworks covering:
Hallucination rate and factual consistency
Relevance and precision/recall
Latency, throughput, and system-level performance
Cost tracking and efficiency
Partner closely with product, engineering, data science, ethics, and infrastructure teams to deliver robust, compliant AI systems.
Communicate technical decisions and findings clearly to cross-functional stakeholders and, where relevant, clients; begin contributing to archit