Senior Director, Knowledge Management & Retrieval Strategy

Overview We are seeking a senior leader to define and scale R&D knowledge and retrieval capabilities that power GenAI experiences across R&D. Key Responsibilities Knowledge Management Leadership Lead and grow a multidisciplinary Knowledge Management organization (Knowledge Graph, Ontology, semantic layer); set vision, priorities, and ways of working. Own the roadmap for R&D knowledge representation (knowledge graph modeling patterns, ontology strategy, semantic layer standards) aligned to GenAI and R&D outcomes. Establish semantic consistency (language, identity, shared truth) across enterprise assets and processes. Promote standard taxonomies and identifiers. Establish mechanisms for quality, reuse, and stewardship of semantic assets. Partner to ensure semantic assets are discoverable, versioned, governed, and consumable via retrieval pipelines and APIs. GenAI Retrieval Architecture Define retrieval strategies for agentic AI and user-facing GenAI. Design semantic retrieval/grounding and contextual data integration approaches. Guide retrieval pipeline development for QA, reasoning, and scientific insights. Establish best practices for RAG in regulated scientific environments. Data Interface & Platform Alignment Harmonize access to enterprise data; define data interface and retrieval API standards. Bridge R&D data users, GenAI product teams, and platform owners. Knowledge Systems & Data Strategy Curate high-value knowledge sources across discovery, development, clinical, and regulatory domains. Define data strategies for integrating structured data, documents, knowledge graphs, and literature. Establish principles for provenance, traceability, and governance. Cross-Functional Collaboration & Governance Translate workflow data needs into data access/retrieval architectures. Ensure retrieval systems support reproducibility, traceability, auditability, and responsible AI in regulated environments. Qualifications Required Life sciences/biomedical/pharma R&D training and experience. Proven leadership of high-performing technical teams (hiring, coaching, performance expectations). Success leading cross-functional programs across product, platform, and governance. Advanced degree in CS, data science, computational biology, bioinformatics, or related. Deep experience designing data architectures/knowledge systems for AI/ML. Strong knowledge of information retrieval, semantic search, and RAG. Experience with large-scale enterprise data platforms. Ability to collaborate across technical, scientific, and platform teams. Preferred Familiarity with omics, clinical data, literature, and regulatory documents. Experience building knowledge graphs/R&D knowledge systems. Exposure to GenAI platforms, agentic systems, and Model Context Protocols (MCPs). Hands‑on ontology engineering/semantic modeling and knowledge graph lifecycle in enterprises. Experience operationalizing a semantic layer to improve consistency. Benefits Vacation: 120 hours/year; Sick time: 40 hours/year (CO/Washington adjusted); Holiday pay (incl. floating): 13 days/year; Work/personal/family: up to 40 hours/year; Parental leave: 480 hours within one year; Bereavement: 240 hours immediate family; Caregiver leave: 80 hours (52-week rolling period); Volunteer: 32 hours/year; Military spouse time-off: 80 hours/year. #J-18808-Ljbffr Scorpion Therapeutics