Staff, AI Product Manager

GSK’s Enterprise AI team turns AI into measurable impact across drug discovery, development, manufacturing, and commercial, with forward deployed teams embedded in the business to build AI products that change outcomes.

This role supports GSK’s manufacturing sites, which make, test, and release our medicines and vaccines safely, compliantly, and at scale. Our ambition is autonomous manufacturing: production processes and support systems (training, workforce planning, quality, maintenance, materials) that plan, adapt, and optimise themselves, freeing people for work that needs human judgement.

As Staff (Director), AI Product Manager for Manufacturing, you will own the manufacturing AI portfolio, shape the vision for autonomous manufacturing, and partner with site and network leadership to back the right use cases and see them delivered, adopted, and scaled.

You will scale existing autonomous programmes, such as training content management and production-floor workforce allocation, and shape what comes next, including autonomous production scheduling. You bring a working understanding of AI, hands-on manufacturing experience, and strong execution and change-management discipline.

Why This Role Exists

Autonomous manufacturing won’t come from isolated pilots. It needs a clear vision, sharp opportunity selection, disciplined delivery, and business teams who own the change. This role brings those together.

In this role, you will:

• Own the manufacturing AI portfolio and roadmap toward autonomous manufacturing.
• Quickly assess which use cases are worth pursuing, backed by evidence.
• Drive delivery from problem framing through deployment, adoption, and value realisation.
• Lead change management so AI solutions are used, trusted, and sustained.
• Act as a trusted partner to manufacturing leadership on AI-driven transformation.

Responsibilities:

This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:

• Define, with leadership, what autonomous manufacturing means for GSK sites, the target state by area, and a staged, funded roadmap.
• Scale the autonomous training content and workforce optimisation programmes to multi-site outcomes.
• Build the case for autonomous production scheduling and other processes, and move the strongest candidates into delivery.
• Make capabilities built at one site (data foundations, agents, optimisation engines) reusable across the network.
• Quickly assess use cases on value, data readiness, feasibility, compliance, and site appetite, and kill weak ideas early.
• Build finance-ready business cases on throughput, OEE, schedule adherence, right-first-time, labour productivity, training cycle time, and cost avoided.

• Own a living view of in-flight, queued, and de-prioritised opportunities with clear rationale, feeding the Enterprise AI portfolio
• Lead engagements end-to-end with FDE and engineering pods, from scope and success criteria through deployment and hand-over.
• Set milestones, manage dependencies across site, IT/OT, quality, and engineering, and clear blockers from prototype to production.
• Make trade-offs when sponsors compete for capacity, and push back on work that won’t move outcomes.
• Build lasting relationships with site, operations, quality, engineering, and learning leaders, and help shape their agenda.
• Co-own change management, from stakeholder mapping and process redesign to training and adoption tracking, so the floor trusts the new way of working.
• Quickly read each site’s processes, culture, systems, and data, and tailor the approach accordingly.
• Coach Senior AI Product Managers on opportunity selection, value cases, and engagement design.
• Engage VP and site leaders, linking AI progress to manufacturing and patient outcomes clearly and honestly.
• Track value realisation against each engagement’s original case using Enterprise AI’s framework, and refine the framework as you learn.
• Run honest post-mortems and feed lessons into how opportunities are selected, delivered, and scaled.
  

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, product management, business, or life sciences.
• 12+ years of experience across pharmaceutical, life sciences, or other regulated manufacturing, and AI/ML, digital, or product leadership roles.
• Experience working at, or directly supporting, a manufacturing production site.
• Experience with AI technologies such as large language models (LLMs), agentic systems, optimisation and scheduling methods, or the ML lifecycle.
• Experience delivering AI or digital initiatives from problem framing through production deployment.
• Experience leading change management in operational environments.
• Experience building business cases for manufacturing or operations initiatives.
• Experience as a trusted partner to senior business leaders (VP and site-head level), leading through credibility and influence.
• Working knowledge of GxP and data-governance constraints in manufacturing, and how they shape AI deployment and validation.
• Experience in one or more of: production scheduling and optimisation, workforce or shift planning, learning and training systems, MES/ERP, or Industry 4.0 / smart factory programmes is a strong plus.
  

Preferred Qualification
If you have the following characteristics, it would be a plus:

• Experience leading AI opportunity discovery and use case triage in manufacturing, including prioritising pipelines, making clear go / no-go calls, and shaping a staged roadmap toward autonomous manufacturing.
• Experience building value cases and investment recommendations that withstand finance and senior manufacturing scrutiny, and managing an AI opportunity portfolio.
• Track record of taking AI engagements to production, from defining scope, success criteria, and exit conditions to scaling point solutions into reusable platforms across sites.
• Fluency across LLMs, agentic systems, optimisation, and ML, with the ability to assess manufacturing data readiness (MES, ERP, LMS, historians, rostering systems) and evaluation design.
• Hands-on use of AI tools to automate product management work, including skills, plugins, and comfort with the command-line interface (CLI).
• Experience navigating GxP, validation, and data-governance requirements when designing AI solutions for manufacturing.
• Experience advising VP and site-head leaders, co-leading change management, and communicating AI impact on manufacturing performance, people, and patients.
• Experience tracking value realisation and adoption, running post-mortems, coaching product teams, and challenging assumptions with evidence.

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 stakeholders. Fully remote work is not available for this position.

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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 diseases – to impact health at scale.

People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.

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