Dir. Product Manager, Digital & Growth AI Tech

GSK•Philadelphia, PA

3d•Hybrid

About The Position

This role sits within GSK’s US Commercial and Digital Experience Technology team and owns the AI-driven commercial growth agenda. It applies generative and predictive AI across the HCP and patient funnel—from awareness and acquisition to conversion, adherence, and loyalty—and measures impact through commercial outcomes such as prescription volume, market share, HCP reach and frequency, patient starts, and persistency. The work takes place in a regulated pharmaceutical environment, including FDA promotional rules, the PhRMA Code, and Medical/Legal/Regulatory (MLR) review. The role sets the AI-for-growth vision and roadmap, partners with engineering and data science to take models from prototype to governed production, and demonstrates commercial impact brand by brand before scaling capabilities across the therapeutic portfolio. It also establishes responsible-AI and promotional governance practices, guides build-versus-buy-versus-partner decisions, runs structured pilots, influences Commercial and regulatory stakeholders, and hires and develops a senior AI product and solutions architecture team.

Requirements

Bachelor’s degree in computer science, engineering, a quantitative field, or life sciences.
10 or more years of product management experience.
At least 2 years shipping AI/ML-powered or generative-AI features into production, rather than only running pilots.
Experience with LLM-based tooling, including prompt or agent design, RAG architectures, or fine-tuning, applied to content generation, personalization, and/or omnichannel orchestration.
Experience with commercial growth mechanics, including brand planning cycles, customer-funnel metrics, market share, and how AI levers affect them.
Experience defining commercial success metrics for AI initiatives, such as prescription volume, market share, and conversion impact, and applying governance and evidence-based criteria to continue, refine, or discontinue initiatives.
Comfort partnering closely with data science and ML engineering on model evaluation, latency, cost, and monitoring trade-offs.

Nice To Haves

Advanced degree in computer science, engineering, a quantitative field, or life sciences.
Pharma, biotech, or healthcare background.
Experience working in a regulated environment.
Experience delivering measurable AI-driven improvements in commercial metrics across two or more funnel stages within two quarters of launch.
Experience developing a documented, repeatable intake-to-production process for AI use cases that earns the trust of Medical, Legal, Regulatory, Compliance, and Data Science stakeholders.
Experience quantifying and communicating AI-driven growth across the HCP and patient journey to Commercial executive leadership while maintaining promotional compliance.

Responsibilities

Own the AI-driven growth capabilities roadmap across the HCP and patient funnel, and report impact using brand-relevant commercial measures such as NRx/TRx, market share, customer reach and frequency, and patient starts.
Define a multi-year roadmap for applied AI across US Commercial and Digital Experience, including generative content engines, conversational AI, predictive customer models, and next-best-action/next-best-offer capabilities, aligned with brand growth targets.
Build autonomous and semi-autonomous agents to generate, test, and optimize creative, targeting, and channel mix for HCP and patient support programs within approved claims and label language.
Lead AI-driven personalization and dynamic content generation that reduces the time from concept to MLR-approved asset and integrates with existing content, campaign-management, and CRM platforms.
Partner with Data Science and ML Engineering to move LLMs, recommender systems, and propensity/next-best-action models from prototype to governed, monitored production services that meet GxP and GSK compliance expectations.
Establish guardrails for model risk, HIPAA and global data privacy, bias testing, and human-in-the-loop review; partner with Medical, Legal, Regulatory, and Compliance on AI use-case intake and MLR-aligned approval for promotional AI.
Make build-versus-buy-versus-partner decisions for AI and foundation-model capabilities, considering growth outcomes, pharmaceutical data privacy, validation requirements, and integration with the existing technology stack.
Run structured pilots with Compliance sign-off and agreed brand-growth metrics; decide whether to scale, refine, discontinue, or pivot initiatives based on results.
Translate between Brand and Commercial Leadership, Medical/Legal/Regulatory, Compliance, and Data Science on current and future responsible uses of AI for growth; brief Commercial executive stakeholders monthly on ROI and opportunities.
Hire and develop a small, senior team of AI-focused product managers and solutions architects embedded in Commercial, and foster a test-and-learn culture grounded in HCP, patient, and brand-performance feedback.