Lead AI Engineer (AI)

Location: Seoul, South Korea; minimum three days per week working in person at a client location or Bain home office; travel beyond the primary working location is required.

Company

Bain & Company is a consulting firm whose AI, Insights & Solutions team designs and delivers AI-powered solutions for clients, from prototypes through enterprise adoption.

What you will do

• Design, develop, and deploy end-to-end generative AI systems, including multi-agent workflows and production-grade applications.
• Build RAG, fine-tuning, embedding, hybrid retrieval, reasoning, tool-use, function-calling, and orchestration components.
• Develop APIs, microservices, CI/CD pipelines, cloud-native deployments, and GenAIOps capabilities with strong observability and reliability.
• Implement evaluation frameworks and automated testing for hallucination, factual consistency, relevance, precision/recall, latency, throughput, cost, and system performance.
• Apply guardrails, fallbacks, red-teaming, human-in-the-loop workflows, and responsible AI principles in partnership with ethics and infrastructure teams.
• Collaborate with product, engineering, data science, infrastructure, ethics, and client stakeholders; communicate technical findings and share knowledge with peers.

Requirements

• 3–5+ years of hands-on experience in software engineering, ML engineering, or applied AI roles.
• Experience shipping generative AI features or systems end-to-end, from prototyping through production.
• Solid prompt engineering, context engineering, and conversation design knowledge.
• Working knowledge of evaluation design, experimentation frameworks, and data-labeling strategies for LLM applications.
• Experience with RAG architectures, agentic patterns, tool use, routing, memory management, ReAct, RLAIF, HITL feedback loops, orchestration frameworks, vector and graph databases, and model/API ecosystems.
• Strong system design, architecture, and production-grade deployment background, including awareness of LLM cost and latency trade-offs.
• Clear communication and effective collaboration across engineering, product, and data science teams.
• Comfort operating in high-ambiguity, cross-functional environments.

Nice to have

• Exposure to hybrid or graph-based retrieval and multi-agent systems.
• Experience supporting or informally mentoring peers.
• Client-facing consulting or enterprise transformation experience.
• Eagerness to grow into a technical leadership role and support junior team members.

Culture & Benefits

• Work in multidisciplinary teams with consultants, product, design, architecture, engineering, data science, ethics, infrastructure, and client stakeholders.
• Learn through Bain’s apprenticeship model, experienced teammates, frequent feedback, and increasing responsibility.
• Contribute to real client deployments and collaborate with major AI ecosystem partners.
• Permanent full-time employment with at least three in-person working days per week and project-based travel.