Staff, AI Product Manager (Development Engine)

Job description

GSK’s Enterprise AI team turns the promise of AI into measurable impact across drug discovery, development, manufacturing, and commercial. Forward deployed teams embed with scientific and business teams to build AI products that change outcomes. This role sits in Chemical Manufacturing & Control (CMC), the function that turns a validated molecule into a reliably manufactured, quality-assured medicine. Its current mission is to double New Product Introductions (NPIs). As Staff AI Product Manager, you’ll own a major slice of our opportunity portfolio, shaping how AI transforms GSK’s process development worldwide. With business stakeholders, you’ll prioritize opportunities by feasibility and value, then structure the problem, size the value, prototype hands-on, and turn it into something a forward deployed engineer (FDE) can build against. You’ll own 10x transformational opportunities in process development acceleration: co-leading self-driving labs and digital twins, advancing in silico modeling and platform models (not point solutions), and agentifying high-value R&D workflows such as document authoring. Working closely with process science data analytics and R&D Tech, you’ll bring creativity grounded in business reality and the execution to deliver measurable impact. Why This Role Exists Forward deployed teams are most powerful when paired with sharp opportunity selection. This role ensures our engineers work on the right things. You will: Own a domain or capability area within the Enterprise AI opportunity portfolio. Identify, size, and shape its highest-value AI opportunities. Partner daily with FDE and full-stack engineering leads to steer engagements end-to-end. Build the business and executive alignment FDEs need to land and scale. Responsibilities: This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following: Find high-value AI opportunities in your domain and rank them by impact, feasibility, and time-to-value. Quantify value rigorously with business cases that withstand finance and senior leadership scrutiny. Spot AI-shaped problems in workflows before the business has articulated them. Co-lead the self-driving labs redesign, defining the 2033 vision and roadmap for lab automation with FDE pods and automation teams. 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. Shape your domain’s portfolio, keeping a living view of in-flight, queued, and de-prioritized opportunities. Make trade-off recommendations when sponsors compete for FDE pods, backed by clear metrics and analysis. Protect engineering focus by pushing back, with evidence, on low-impact opportunities. Partner with FDE and full-stack leads, turning ambiguous problems into clear problem statements, prototypes, and success metrics. Shape engagements end-to-end: scope, success criteria, exit conditions, and scaling paths. Drive reuse by turning one-off solutions into platform capabilities. Engage VP-level leaders to turn ambitions into concrete, fundable AI engagements. Build sponsor coalitions that secure data access, change commitment, and air cover. Communicate impact in terms of patients, science, and enterprise outcomes. Apply the value-realization framework to every engagement and refine it as you learn. Run honest post-mortems and feed lessons into opportunity selection. Why You? Basic Qualification We are seeking professionals with the following required skills and qualifications to help us achieve our goals: 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, artificial intelligence/machine learning (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 working in at least one area of the pharmaceutical value chain: research and development (R&D), clinical, manufacturing, or commercial. Experience applying AI/ML technologies such as large language models (LLMs), agentic systems, knowledge graphs, or data engineering. Experience building business cases and sizing value for R&D initiatives. Experience in product management or product 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 in partnership with scientists and automation teams. Experience partnering with data analytics, data science, or process science teams on modeling, optimization, and simulation. Experience working as a senior individual contributor, leading through influence rather than direct reports. Preferred Qualification If you have the following characteristics, it would be a plus: 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 research and development (R&D), clinical, or supply chain, including building a pipeline ranked 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, and scaling pathways, and turning 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 This role follows a hybrid working model based in the United States. You will spend scheduled time on-site to collaborate and engage with your team and stakeholders. Fully remote work is not available for this position. #LI-GSK #AGTech 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. Why GSK? Uniting science, technology and talent to get ahead of disease together. GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious dis