Staff, AI Product Manager (Development Engine)

Join GSK’s Enterprise AI team as a Staff AI Product Manager focused on Chemical Manufacturing & Control (CMC). This hybrid role in Collegeville, PA helps drive measurable growth by targeting double New Product Introductions (NPIs). You will own high-value AI opportunities that accelerate process development, including self-driving labs, digital twins, in silico modeling, and agentifying R&D workflows. If you enjoy translating ambiguous opportunities into fundable, scalable programs that stand up to executive scrutiny, this role is built for you.

Responsibilities

• Own a domain or capability area within GSK’s Enterprise AI opportunity portfolio.
• Identify, size, and shape the highest-value AI opportunities in your domain.
• Partner daily with FDE and full-stack engineering leads to guide engagements end-to-end.
• Drive executive alignment and build the business case needed to land and scale AI initiatives.
• Discover, rank, and continuously refine opportunities by impact, feasibility, and time-to-value.
• Quantify value with rigorous business cases that finance and senior leadership can evaluate.
• Spot AI-shaped problems in workflows before they are fully articulated by the business.
• Co-lead the redesign of self-driving labs, defining a 2033 vision and roadmap for lab automation with FDE pods and automation teams.
• Help drive 10x in silico modeling by co-leading the digital twin agenda with an end-to-end platform mindset.
• Accelerate molecule onboarding by defining platform fitness and tracking progress toward halving development time.
• Maintain a living view of in-flight, queued, and de-prioritized opportunities.
• Recommend trade-offs when sponsors compete for FDE pods, using clear metrics and analysis.
• Protect engineering focus by pushing back on low-impact opportunities with evidence.
• Turn ambiguous challenges into problem statements, prototypes, and success metrics.
• Shape engagements end-to-end: scope, success criteria, exit conditions, and scaling paths.
• Increase reuse by converting one-off solutions into platform capabilities.
• Engage VP-level leaders to convert ambitions into concrete, fundable AI engagements.
• Build sponsor coalitions to secure data access, change commitment, and executive air cover.
• Communicate impact in terms of patients, science, and enterprise outcomes, applying a value-realization framework to every engagement.
• Run honest post-mortems and feed lessons into future opportunity selection.

Requirements

• Bachelor’s degree or equivalent experience in technology, computer science, product management, or a related field.
• 10+ years of experience across pharmaceutical or life sciences, AI/ML product strategy, or senior product management or strategy roles in technology-led organizations.
• Experience leading technology or AI initiatives from problem framing through funding and into delivery.
• Experience across at least one area of the pharmaceutical value chain: R&D, clinical, manufacturing, or commercial.
• Experience applying AI/ML such as LLMs, agentic systems, knowledge graphs, or data engineering.
• Experience building business cases and sizing value for R&D initiatives.
• Experience in product management/strategy, including opportunity sizing, roadmap development, and prototyping.
• Experience with modeling, digital twins, self-driving labs, or physical AI initiatives in pharmaceutical R&D or process development, including defining pilots and evaluating results with scientists.
• Experience defining a vision and roadmap for self-driving labs and lab automation with scientists and automation teams.
• Experience partnering with data analytics, data science, or process science teams on modeling, optimization, and simulation.
• Experience leading as a senior individual contributor through influence rather than direct reports.

Preferred Qualification

• Master’s or PhD in technology, computer science, product management, or a related field.
• Ability to use evidence from rapid prototyping to challenge engineering choices and scope work realistically.
• Experience leading AI opportunity discovery and problem framing across a major domain (such as R&D, clinical, or supply chain), including building a ranked pipeline by impact, feasibility, and time-to-value.
• Experience co-leading self-driving lab or lab automation initiatives, including automating experiment planning, execution, and data capture, and linking labs to in silico models.
• Experience building value cases and investment recommendations that withstand finance and senior leadership scrutiny, and managing an opportunity portfolio.
• Experience scoping AI engagements end-to-end, including success criteria, exit conditions, scaling pathways, and converting one-off solutions into reusable platform capabilities.
• Technical fluency in AI/machine learning, data, and evaluation design, with hands-on use of AI tools and command-line interfaces to automate daily work.
• Experience working within good practice (GxP), regulatory, and data-governance requirements in a regulated environment.
• Experience influencing vice president-level leaders without direct authority, communicating AI impact in terms of patients, science, and business outcomes, and using outcome tracking and post-mortems to improve future work.

Work Arrangement

• Hybrid working model based in the United States.
• Scheduled time on-site is required for collaboration with the team and stakeholders.
• Fully remote work is not available.

Technologies: large language models (LLMs), agentic systems, knowledge graphs, data engineering, digital twins, self-driving labs, physical AI.