AI Team Lead

Global Pharmaceutical Company | Germany | Hybrid | PermanentWant to lead an AI team where the work could help bring new medicines to patients faster? This is a hands-on leadership role at one of the world's leading research-driven pharmaceutical companies, building LLM and agentic AI systems across drug discovery and clinical development.About the CompanyA global, research-driven pharmaceutical company operating across 100+ markets, with a pipeline spanning small molecules, biologics and precision medicine. AI is a core part of the company's long-term strategy, backed by dedicated AI teams, academic partnerships and a clear commitment to deploying AI responsibly in a GxP-regulated environment.The RoleAs AI Team Lead, you will own the technical leadership of a cross-functional AI squad working on high-priority use cases across the drug development lifecycle. You will set direction for a team of ML Engineers, Data Scientists and AI Platform specialists while staying close to the code.You will architect LLM and agentic solutions, make key build-vs-buy decisions and take systems into production to the standard a regulated environment demands. You are the bridge between AI research ambition and engineering reality.What You Will DoTechnical LeadershipLead the design and deployment of LLM-based systems, RAG architectures and agentic AI workflows across research and clinical use casesDefine the team's approach to model selection, prompt engineering, fine-tuning and evaluationTeam & DeliveryLead and mentor a team of 4 to 8 AI and ML Engineers, running technical reviews and building a high-performance cultureOwn delivery across the team's roadmap, balancing exploration with production-grade executionAI in a Regulated ContextEnsure AI systems align with GxP guidelines, data governance requirements and the EU AI ActImplement model monitoring, drift detection and retraining pipelines for high-stakes decision supportChampion responsible AI: explainability, bias assessment and human-in-the-loop designWhat You BringHands-on experience building and deploying LLM-based systems, RAG pipelines and agentic AI applications in productionProven technical leadership: setting architecture direction, reviewing code and mentoring engineersStrong Python and MLOps fundamentals (versioning, monitoring, CI/CD)Experience in or alongside a regulated industry such as pharma, medtech or financial servicesConfidence presenting to senior non-technical leaders without losing depth with engineersFluent English; German is a plus but not requiredNice to HaveLife sciences AI use cases such as literature mining, clinical NLP or regulatory document intelligenceKnowledge of GxP validation frameworks (GAMP5, 21 CFR Part 11, EU Annex 11)Experience with knowledge graphs or biomedical ontologies (MeSH, SNOMED, Gene Ontology)A track record of taking an AI team from proof of concept to sustained production delivery #J-18808-Ljbffr