Senior Director, Lab-to-Product Platform and Operations Technology

1. Own and operate core lab, plant, and external partner operational platforms Lead the digital capabilities that support lab operations across Research, CMC, and QC, including LIMS, ELN/LES, sample & inventory management, registration, lab automation enablement, instrument integration, lab computing, lab system validation, and operational data capture. Oversee plant-floor operational technologies (OT) such as equipment/instrument connectivity, environmental and facility monitoring interfaces, materials tracking, barcode/RFID data capture, and automated data collection (excluding MES and supply chain systems). Enable operational technology connectivity, workflow interoperability, and validated data exchange with CROs, external research labs, development partners, contract testing labs, and external manufacturers. Support validated data handoffs, sample/material traceability, workflow tracking, and operational interfaces across hybrid (internal + external) execution models. Ensure reliability, compliance, validated state, lifecycle management, and service continuity across internal systems and partner-connected operational interfaces. Oversee lab/operational system validation activities in partnership with Quality to maintain GxP compliance and data integrity across all execution environments. Build the Lab-to-Product Platform (Internal + External Execution Model) Architect and deliver the operational platform that connects experiment execution → sample workflows → QC testing → plant operational activities → external execution and release workflows. Provide reusable platform components including metadata standards, workflow modules, instrument connectors, validated integration frameworks, and operational data pipelines that external partners can adopt or interface with. Ensure seamless interoperability with: Establish secure, scalable, validated patterns for partner connectivity (e.g., APIs, secure file exchange, partner portals, event/data streams). Deliver robust operational data integration Work closely with the Data & AI organization to ensure operational data - including external partner-generated data - is structured, contextualized, and AI-ready. Implement consistent metadata, data capture, and validated interface practices across internal and external operations. Enable cross-system visibility into workflows, materials, samples, and processes across internal labs, plants, and external partner networks. Collaborate with ReDev Technology, Manufacturing/CMC/Supply Chain Technology, Quality, Tech Operations, Data/AI, Infrastructure, and Security to ensure cohesive integration and operational excellence. Required Bachelor's degree in Computer Science, Engineering, Life Sciences, or related field (or equivalent experience). 15+ years of progressive leadership experience in laboratory informatics, scientific operations, OT/plant-floor (shop floor) automation enablement, or manufacturing operational technology in biotech/pharma. Deep expertise with lab operations systems (e.g., LIMS, ELN/LES, sample/inventory management, workflow orchestration), lab computing environments, instrument integration, and validated interfaces. Experience supporting operational workflows across internal and external networks, including CROs, external research labs, contract testing labs, and/or external manufacturers. Strong understanding of GxP, Computer System Validation (CSV), data integrity, interoperability, and operational data management. Experience leading product management and engineering/architecture teams in regulated and non-regulated environments. Proven track record delivering enterprise-scale operational platforms with measurable impact. Exceptional communication, influence, and stakeholder-management skills. Ability to balance long-term strategy with pragmatic execution. Advanced degree in Computer Science, Engineering, or Life Sciences. Experience supporting RNAi, oligonucleotide, or other advanced modality development or manufacturing. Familiarity with modern integration architectures (APIs, event-driven patterns), lab automation frameworks, OT/plant-floor technologies, and emerging AI-driven automation. Experience in environments where R&D, CMC, QC, Manufacturing, and external partners depend on shared operational platforms and validated systems.