General Manager, Canada, Toronto

A 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. Responsibilities

Full P&L ownership: budget, forecast, pricing, margin, and exception approvals Lead quarterly business reviews and corrective actions with executive leadership Establish and enforce operating metrics for bookings, backlog, capacity, utilization, project margin, and cash collection Manage project intake, scoping, staffing, scheduling, risk, and escalationsStandardize delivery practices, milestone reporting, and program governance Optimize throughput and cycle time while maintaining scientific rigor and data quality Oversee software and AI/LLM rollout, adoption, training, and stabilization Lead integration of software-enabled workflows connecting wet-lab and AI capabilitiesAlign systems, templates, SOPs, and reporting across sites Build and scale a high-performing team with clear accountability and measurable metrics Maintain safe laboratory operations and audit readiness Qualifications

15+ years of management experience with P&L, budgeting, forecasting, and margin control 5+ years in CRO, CDMO, or fee-for-service biologics R&D services 8+ years leading managers and senior scientific or operational leaders Proven track record scaling operations, implementing processes, and driving change Experience leading software rollouts and integrating AI/LLM tools in operations Strong client-facing leadership, program review, and escalation management experienceExperience in fee-for-service, non-GMP lab environments Multi-site and cross-geography experience preferred Familiarity with in silico, computational biology, and AI-assisted biologics workflows

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