Experteer Overview In this senior AI Engineer role, you will own end-to-end AI delivery within Roche’s AI Engineering Cluster, shaping scalable GenAI-driven solutions for Pharma Technical Operations. You contribute to architecture, data pipelines, evaluation, and production operations, collaborating with IT, QA, and business teams to deliver measurable value. You’ll lead technical delivery, mentor engineers, and ensure solutions are compliant, reliable, and impactful. This is an opportunity to influence AI-enabled processes in a regulated manufacturing environment and advance patient outcomes.

Compensaciones / Incentivos • Own end-to-end technical delivery of AI solutions from problem understanding to continuous improvement • Design scalable AI architectures (data flows, model integration, APIs, UIs, production infra) • Develop GenAI and agentic AI solutions with RAG, multi-step workflows, tool-using agents, and evaluation methods • Maintain engineering quality through automated testing, CI/CD, observability, and documentation • Ensure production AI solutions are reliable, secure, cost-aware,



and continuously improved • Define success metrics linking business needs to technical outcomes • Develop evaluation frameworks and AI engineering harnesses for repeatable experimentation • Manage lifecycle of deployed agents including versioning, testing, monitoring, and retirement • Collaborate with stakeholders to translate operational challenges into AI-enabled products • Lead technical delivery, mentor engineers, and influence cross-functional partners • Promote responsible AI, compliance, and data governance in regulated environments

Responsabilidades • Bachelor’s degree or equivalent practical experience • Proven track record delivering production-grade software, AI, or analytics solutions • Strong hands-on Python experience and software engineering practices • Experience designing/delivering cloud-based or hybrid apps, preferably AWS • Hands-on experience with agent frameworks and harnesses (e.g., DeepAgents, LangGraph, LangChain) • Solid understanding of LLMs, RAG, prompt engineering, AI agents, model integration, and tool usage • Experience with APIs, microservices, CI/CD, Docker, monitoring, automated testing, and code reviews • Ability to translate evaluation results into engineering decisions and product improvements • Ability to lead technical delivery, manage ambiguity, and influence stakeholders • Experience in regulated environments (pharma/biotech/quality) preferred

Requisitos principales •

📌 AI Engineer (Madrid)
🏢 Roche
📍 Madrid