Dir. Product Manager, Digital & Growth AI Tech

This role sits in the US Commercial and Digital Experience Technology team and owns the growth agenda: using generative and predictive AI to accelerate HCP and patient outcomes across the full commercial funnel — awareness, acquisition, conversion, adherence, and loyalty — and translating that into measurable brand growth (NRx/TRx lift, share, HCP reach and frequency, patient persistency). Every capability operates inside a heavily regulated pharma environment: FDA promotional rules, PhRMA Code, and Medical/Legal/Regulatory (MLR) review. You set the AI-for-growth vision, build the models-to-production pipeline in partnership with engineering and data science, and prove commercial impact brand by brand before scaling across the therapeutic portfolio.    This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:  • Commercial Growth Agenda: Own the AI-driven growth capabilities roadmap across the HCP and patient funnel — awareness, acquisition, conversion, adherence/persistency, and loyalty — reporting impact in brand-relevant commercial terms (NRx/TRx, market share, customer (HCP, Patients) reach/frequency, patient starts rather than generic marketing metrics.  • AI Product Vision for Commercial Growth: Define the multi-year roadmap for applied AI across US Commercial and Digital experience — generative content engines, conversational AI, predictive customer (HCP and patient) models, next-best-action/next-best-offer — anchored to brand growth targets set with Commercial Leadership and Brand teams.  • Growth AI Agents: Build autonomous and semi-autonomous agents that generate, test, and optimize creative, targeting, and channel mix for customer (HCP and patient) support programs in real time, within approved claims and label language.  • Personalization at the Point of Prescribing/Care: Lead AI-driven personalization and dynamic content generation that shortens concept-to-MLR-approved-asset time, that plug into existing content and campaign management, CRM etc. platforms, reducing time from concept to MLR-approved asset.  • Model-to-Production for Commercial Use Cases: Partner with Data Science/ML Engineering to move growth models (LLMs, recommender systems, propensity/NBA models) from prototype to governed, monitored production services that meet GxP and GSK compliance expectations.  • Responsible AI & Pharma Regulatory Governance: Establish guardrails for model risk, HIPAA and global data-privacy equivalents, bias testing, and human-in-the-loop review; partner with Medical, Legal, Regulatory, and Compliance on an AI use-case intake and MLR-aligned approval process specific to promotional AI. • AI Investment Strategy (Build-vs-Buy-vs-Partner): Decide which AI/foundation-model vendors and capabilities to pursue for growth outcomes, factoring in pharma-specific data-privacy and validation requirements. Ensure AI capabilities plug cleanly into the existing tech stack rather than creating parallel systems. • Experimentation & Commercial Proof of Value: Run structured pilots — with Compliance sign-off — against brand-growth success metrics (Rx lift, conversion, patient starts, cost per acquisition) before greenlighting portfolio-wide rollout; kill or pivot underperforming bets quickly. • Cross-Functional Influence in Commercial: Act as the primary translator between Brand/Commercial Leadership, Medical/Legal/Regulatory, Compliance, and Data Science on what AI can responsibly do today vs. next year for growth; brief Commercial executive stakeholders monthly on ROI and opportunities. • Talent & Team Build: Hire and develop a small, senior team of AI-focused product managers and solutions architects embedded in Commercial; instill a test-and-learn culture grounded in real HCP, patient, and brand-performance feedback. Why You? Basic Qualification  We are seeking professionals with the following required skills and qualifications to help us achieve our goals: • Bachelor's degree in computer science, engineering, quantitative, or life-sciences • 10+ years in product management with at least 2 years shipping AI/ML-powered or generative-AI features into production (not just pilots). • Experience with LLM-based tooling — prompt/agent design, RAG architectures, or fine-tuning — applied to content generation, personalization and/ or omnichannel orchestration • Experience in commercial growth mechanics: brand planning cycles, customer funnel metrics, market share, and how AI levers move each.  • Experience defining success metrics for AI initiatives in commercial terms, such as prescription volume, market share, and conversion impact, and using established governance and evidence-based criteria to continue, refine, or discontinue initiatives that do not meet agreed thresholds.  • Comfort partnering closely with data science/ML engineering on model evaluation, latency, cost, and monitoring trade-offs.  Preferred Qualification If you have the following characteristics, it would be a plus  • Advanced degree in computer science, engineering, quantitative, or life-sciences field.  • Pharma, biotech, or healthcare background is strongly preferred  • Experience working within a regulated environment.  • Experience delivering measurable, AI-driven improvements in commercial metrics—such as prescriptions, market share, HCP reach and frequency, or patient starts—across two or more funnel stages within two quarters of launch.  • Experience developing a documented, repeatable intake-to-production process for new AI use cases that earns the trust of Medical, Legal, Regulatory, Compliance, and Data Science stakeholders.  • Experience quantifying and communicating how AI drives growth across the HCP and patient journey to Commercial executive leadership, while maintaining promotional compliance.  Working arrangement  This role is hybrid and based in the United States. You will spend scheduled time on-site for collaboration and stakeholder engagement. Remote work is supported as part of a hybrid arrangement.  #Li-GSK  #AGTec  Skills AI Platforms, Change Management, Data Analysis, Feature Prioritization, Machine Learning Model Management, ML Platforms, Model Evaluation, Performance Analysis, Product Delivery, Product Design, Product Lifecycle Management (PLM), Product Roadmapping, Roadmap Development, Statistical Analysis, User Needs Analysis Please visit  GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.