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Staff, AI Product Manager (Development Engine)

GlaxoSmithKline Collegeville, PA

Collegeville, PA

Today

Full time Agentic Ai Ai Workflows Ai/ml Product Management

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Job Description

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.

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