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 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 language, identity, and semantic consistency so systems/people/analytics/AI operate from shared truth. Promote standard taxonomies and identifiers across the organization. Establish mechanisms for quality, reuse, and stewardship of semantic assets (definitions, taxonomies/ontologies, entity models, metadata). Partner with platform, governance, and product teams to ensure semantic assets are discoverable, versioned, governed, and consumable via retrieval pipelines and APIs. Define GenAI retrieval strategies (agentic AI and user-facing applications), semantic retrieval/grounding, and retrieval pipelines for QA/reasoning/scientific insight generation; establish RAG best practices in regulated environments. Harmonize access to enterprise data assets; define standards for data interfaces and retrieval APIs; align GenAI needs with enterprise data infrastructure strategy. Partner to identify/curate high-value knowledge sources across discovery, development, clinical, and regulatory domains. Establish principles for data provenance, traceability, and governance in AI-assisted scientific workflows. Ensure retrieval systems meet standards for reproducibility, traceability, auditability, and responsible AI use in regulated environments. Qualifications Required : Formal training/experience in life sciences, biomedical research, or pharmaceutical R&D. Proven experience leading/developing high-performing technical teams (hiring, coaching, performance expectations). Demonstrated success leading cross-functional programs aligning product, platform, and governance around shared roadmaps and outcomes. Advanced degree (CS, data science, computational biology, bioinformatics, or related). Deep experience designing data architectures/knowledge systems for AI/ML. Strong understanding of information retrieval, semantic search, and RAG. Experience with large-scale enterprise data platforms. Ability to collaborate across technical, scientific, and platform teams. Preferred : Knowledge of scientific data modalities (omics, clinical, literature, 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 practices. Experience defining/operationalizing a semantic layer. Benefits (as stated) Eligible for Company long-term incentive program. Vacation: 120 hours/year; Sick time: 40 hours/year (Colorado 48; Washington 56); Holiday pay: 13 days/year; Work/Personal/Family time: up to 40 hours/year; Parental leave: 480 hours; Bereavement leave; Caregiver leave; Volunteer leave; Military spouse time-off. #J-18808-Ljbffr Scorpion Therapeutics