Job Title

General Manager, Canada Full-Time On-SiteA rapidly growing biologics discovery and development organization is seeking an experienced operational leader to drive its Canadian site through a critical growth phase. The site delivers biologics services to pharmaceutical and biotech clients, integrating in silico and AI-driven approaches into scientific workflows. The General Manager will own P&L, operational performance, and site scaling, while implementing software and AI-enabled tools to improve throughput, predictability, and client satisfaction.ResponsibilitiesFull P&L ownership: budget, forecast, pricing, margin, and exception approvalsLead quarterly business reviews and corrective actions with executive leadershipEstablish and enforce operating metrics for bookings, backlog, capacity, utilization, project margin, and cash collectionManage project intake, scoping, staffing, scheduling, risk, and escalationsStandardize delivery practices, milestone reporting, and program governanceOptimize throughput and cycle time while maintaining scientific rigor and data qualityOversee software and AI/LLM rollout, adoption, training, and stabilizationLead integration of software-enabled workflows connecting wet-lab and AI capabilitiesAlign systems, templates, SOPs, and reporting across sitesBuild and scale a high-performing team with clear accountability and measurable metricsMaintain safe laboratory operations and audit readinessQualifications15+ years of management experience with P&L, budgeting, forecasting, and margin control5+ years in CRO, CDMO, or fee-for-service biologics R&D services8+ years leading managers and senior scientific or operational leadersProven track record scaling operations, implementing processes, and driving changeExperience leading software rollouts and integrating AI/LLM tools in operationsStrong client-facing leadership, program review, and escalation management experienceExperience in fee-for-service, non-GMP lab environmentsMulti-site and cross-geography experience preferredFamiliarity with in silico, computational biology, and AI-assisted biologics workflows