Experteer Overview
In this role you design, build, and deploy generative AI systems for Bain’s AIS team, delivering AI-enabled transformations at scale. You lead technical delivery across workstreams, bridging individual contribution and mentorship while partnering with cross-functional teams and client stakeholders to achieve enterprise impact. You’ll shape multi-component AI pipelines, integrate safety and governance, and drive production-ready solutions. This is a growth-focused, leadership-forward engineering role in a collaborative, innovation-driven environment.

Compensaciones / Incentivos
• Own design, development, and deployment of generative AI systems and multi-agent workflows in client engagements
• Architect and build AI pipelines (RAG, fine-tuning, embeddings, hybrid retrieval)
• Develop agentic systems with scalable tool integration and memory management
• Lead workstreams from research to production deployment with quality and cadence
• Build APIs, microservices, CI/CD, and cloud-native deployments with observability
• Establish GenAIOps processes for automated testing, latency monitoring, and continuous improvement
• Implement guardrails, HITL workflows, and responsible AI considerations in system design
• Mentor junior engineers and contribute to architecture discussions at program level
• Collaborate with product, engineering, data science, ethics,



and infra teams to deliver robust AI systems
• Communicate technical decisions clearly to cross-functional teams and clients
• Foster a culture of technical excellence, learning, and inclusion within AIS

Responsabilidades
• 6-11+ years in software/ML engineering or applied AI with hands-on delivery
• Proven experience shipping generative AI features end-to-end with ownership of full workstreams
• Emerging leadership presence; ability to guide peers and coordinate workstreams
• Strong communication skills for non-technical stakeholders
• Solid prompt and context engineering skills; familiarity with conversation design
• Experience with evaluation design and data labeling for LLM apps
• Proficiency in RAG architectures, agentic patterns, HITL methodologies
• Experience with AI frameworks, orchestration tools, vector/graph databases, and API ecosystems
• Strong system design, architecture, and production-grade deployment
• Understanding of cost and latency tradeoffs in LLM workloads
• Comfort working in high-ambiguity, cross-functional environments
• Eagerness to grow into full technical leadership and develop others
• Experience in client-facing consulting or enterprise transformation (a plus)

Requisitos principales
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📌 Manager, AI Engineering (Madrid)
🏢 Bain u0026
📍 Madrid