Lead, AI Engineering

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We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.

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.

The Lead AI Engineer will design, build, and ship generative AI systems and agentic solutions for Bain’s clients. You will contribute across the full development lifecycle — from early experimentation and prototyping through to production deployment — collaborating closely with senior engineers, product managers, and data scientists. This is a hands‑on individual contributor role with growing influence on technical direction and an opportunity to begin mentoring more junior team members.

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.

• Contribute to the design, development, and deployment of end‑to‑end generative AI systems, including multi‑agent workflows and production‑grade AI applications.
• Build and iterate on 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 reasoning, tool use, function calling, and orchestration across AI workflows
• Build and contribute to agentic systems, applying sound engineering principles around separation of concerns, memory architecture, and tool integration
• Contribute across the full stack: model experimentation, evaluation design, and production system deployment
• Build and maintain APIs, microservices, CI/CD pipelines, and cloud‑native deployments with attention to observability and reliability
• Support and help build 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‑team 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,…