Lead, AI Engineering

Location: Lisbon or Madrid, EMEA. Hybrid work is required, with a minimum of three days per week in person at a Bain office or client location; travel beyond the primary working location is required based on project needs.

Company

Bain & Company’s AI, Insights & Solutions team designs and delivers AI-powered solutions with measurable business impact for clients.

What you will do

• Design, develop, and deploy end-to-end generative AI systems, multi-agent workflows, and production-grade AI applications.
• Build AI pipelines covering RAG, fine-tuning, embedding optimization, hybrid retrieval, reasoning, tool use, function calling, and orchestration.
• Develop APIs, microservices, CI/CD pipelines, cloud-native deployments, and GenAIOps processes with strong observability and reliability.
• Design evaluation frameworks and automated evaluation suites for hallucination, factual consistency, relevance, performance, latency, throughput, cost, and continual improvement.
• Implement guardrails, fallbacks, red-teaming, human-in-the-loop workflows, and responsible AI practices in partnership with ethics teams.
• Collaborate with product, engineering, data science, infrastructure, ethics, consultants, and clients; communicate technical findings and support technical learning.

Requirements

• 3–5+ years of hands-on experience in software engineering, ML engineering, or applied AI, including building responsibilities.
• Experience shipping generative AI features or systems end-to-end, from prototyping through production.
• Experience with RAG architectures, including vector-based retrieval; knowledge of hybrid or graph-based retrieval, agentic patterns, tool use, routing, memory management, and multi-agent systems.
• Experience with ReAct, RLAIF, HITL workflows, feedback loops, orchestration frameworks, vector and graph databases, and model and API ecosystems.
• Solid prompt engineering, context engineering, and conversation design skills.
• Working knowledge of evaluation design, experimentation frameworks, and data-labeling strategies for LLM applications.
• Strong system design, architecture, and production deployment background, including awareness of LLM cost and latency trade-offs.
• Clear communication skills and the ability to explain technical concepts to non-technical stakeholders.
• Ability to work in high-ambiguity, cross-functional environments and eagerness to grow into technical leadership while supporting junior team members.

Nice to have

• Experience supporting or informally mentoring peers.
• Experience with hybrid or graph-based retrieval and multi-agent systems.
• Client-facing consulting or enterprise transformation experience.

Culture & Benefits

• Work in multidisciplinary teams using Bain’s apprenticeship model, with experienced teammates, frequent feedback, and increasing responsibility.
• Opportunities to collaborate with major AI ecosystem partners on real client deployments.
• Broad learning and growth opportunities across complex client problems and enterprise transformations.
• Permanent full-time employment.
• In-person collaboration at least three days per week and project-dependent travel are required.

Hiring process

• Submit an application by 30 October 2026.