Expert Senior Manager, AI Engineering

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 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 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.

• 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 tuning
  • Embedding generation and optimization
  • Hybrid retrieval strategies (vector, graph, keyword)
• 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.
• 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.
• 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) 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 build robust, compliant AI systems.
• 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…