Experteer Overview

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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 / Ventajas

- 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; xugodme 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