Life Sciences Supply Chain Manufacturing Ops & AI Transformation Delivery- Senior Manager

Location:

Anywhere in Country

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Client-facing Life Sciences manufacturing transformation leader accountable for shaping and delivering technology-enabled programs that improve manufacturing performance, quality, compliance, and supply reliability. The role combines regulated plant-floor expertise with data, AI, automation, and disciplined program delivery.

As a Senior Manager in Supply Chain Manufacturing, you will lead transformation programs for pharmaceutical, biotechnology, and medical-device manufacturers, from defining the operational problem and value case through solution design, implementation, adoption, stabilization, and measurable results. You will work across manufacturing, quality, laboratory, engineering, supply chain, and technology teams to connect plant operations with enterprise systems and data.

This is a techno-functional delivery role. You will need the credibility to redesign manufacturing processes and operating models, and the fluency to direct teams delivering manufacturing execution, automation, integration, data, and AI solutions. You will remain accountable for delivery quality, risk, client relationships, and outcomes in regulated environments. “The Life Sciences focus reflects the practice’s emphasis on connected manufacturing and quality workflows across process, batch, and discrete operations, including electronic batch records, electronic device history records (eDHRs), traceability, and integration across plant and enterprise systems.”

• Lead end-to-end Life Sciences manufacturing transformations, from assessment and mobilization through design, deployment, stabilization, and value realization.
• Build trusted relationships with senior manufacturing, quality, MS&T, engineering, supply chain, digital, and IT/OT stakeholders; establish governance and drive timely decisions.
• Translate priorities such as yield, throughput, right-first-time execution, deviation reduction, batch-cycle time, asset reliability, and supply continuity into practical workplans and outcome measures.
• Direct multidisciplinary teams across manufacturing process design, MES/MOM, automation, data engineering, AI, architecture, integration, quality, change management, testing, and deployment.
• Lead solution and process design for batch and discrete execution, electronic batch records, electronic device history records (eDHRs), recipes and routings, material and product genealogy, review by exception, maintenance, quality workflows, and plant performance management.
• Guide integration across MES/MOM, ERP, LIMS, QMS, historians, SCADA, DCS/PLC, asset-management systems, and relevant cloud or edge platforms.
• Establish trusted manufacturing data foundations through appropriate data models, asset and process context, master data, metadata, lineage, governance, and secure IT/OT connectivity.
• Shape analytics and AI use cases, such as process monitoring, predictive maintenance, deviation investigation support, digital twins, and decision support; assess their value, data readiness, workflow fit, and risks before scaling.
• Partner with client quality and validation teams to incorporate applicable GxP controls, data integrity, electronic-record requirements, change control, and risk-based assurance into delivery plans. The applicable controls will depend on the product, system, and intended use.
• Manage scope, schedule, budget, staffing, dependencies, quality, risks, issues, and contractual commitments; guide testing, cutover, training, adoption,…