Expert Senior Manager, AI-ML Engineering

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

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 and 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. Our collaborative and supportive environment fosters creativity and continuous learning, enabling us to consistently deliver exceptional results.

The AI Engineering Expert Senior Manager 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.

• 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‑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, 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 including RAG, agents, prompt engineering, and AI safety

• 8–12+ years in software engineering, ML engineering, or applied AI roles with significant hands‑on building responsibilities
• Demonstrated experience leading complex, multi‑stack generative AI programs from conception through production
• Str…