We are currently the top ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 overall spot a record seven times. 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 r obust AI applications that can be piloted, scaled, and adopted.
As a Manager, AI Engineering in AIS, you will lead the technical delivery of these transformations, bridging individual contribution and team leadership to move solutions from prototype to real adoption. You will take ownership of workstreams, guide more junior engineers, and interface with cross-functional partners and client stakeholders to ensure technical work lands with measurable enterprise impact.
The Role The Manager, AI Engineering will design, build, and ship generative AI systems and agentic solutions for Bain's clients — while beginning to lead others in doing the same. This role sits at the inflection point between senior individual contributor and emerging technical leader. 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. Own the design, development, and deployment of generative AI systems and multi-agent workflows within client engagements, taking end-to-end accountability for assigned workstreams.
Hybrid retrieval strategies (vector, graph, keyword)
Drive workstreams from research and experimentation through production deployment, maintaining quality and pace.
Build and maintain APIs,



microservices, CI/CD pipelines, and cloud-native deployments with strong attention to observability and reliability.
Establish and improve 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 general ethics teams to ensure alignment with Bain's Responsible AI standards
Latency, throughput, and system-level performance
Partner closely with product, engineering, data science, ethics, and infrastructure teams to deliver robust, compliant AI systems.
Actively mentor and develop more junior engineers (Associates, Senior Associates, Leads), sharing knowledge on RAG, agents, prompt engineering, and AI safety best practices.
Contribute to a culture of technical excellence, learning, and inclusion within the AIS engineering community.
6 -11+ years in software engineering, ML engineering, or applied AI roles, with significant hands-on building experience.
~ Solid prompt engineering and context engineering skills; Strong working knowledge of evaluation design, experimentation frameworks, and data labeling strategies for LLM applications.
~ hybrid or graph-based approaches a plus)
~ ReAct, RLAIF, and other HITL + feedback loop methodologies
~ AI-specific tools & frameworks — orchestration frameworks, vector and graph databases, model + API ecosystems

Strong background in system design, architecture, and production-grade deployment.
This role requires a minimum of three days per week working together in person, either at a client location or at your Bain home office.
Travel is required beyond your home office / primary working location. Frequency and destination vary by project needs.
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📌 Engineering Manager (Madrid)
🏢 Bain
📍 Madrid