Manager II, AI Product
Company: Glaxosmithkline
Location: UK – London – New Oxford Street (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-11-06
About this role
# About the Role
GSK’s Enterprise AI team translates the promise of AI into measurable impact across drug discovery, development, manufacturing, and commercial. Forward deployed engineers (FDEs) and full-stack engineers embed directly with scientific and business teams to build AI products that change outcomes.
We are hiring a Product Manager II, AI Product Manager to support our forward deployed teams working with GSK’s manufacturing sites. This is an individual contributor role for someone early- to mid-career who is hungry to do the analytical, hands-on, and stakeholder-facing work that makes AI engagements succeed: opportunity discovery, value sizing, scoping, hands-on prototyping, delivery, and ongoing measurement. You will be supported by senior team members, but the work — the briefs, the analyses, the value cases, the scoping docs, and getting things over the line — will be yours to drive.
This role is execution first. You will work directly with site teams in production, planning, quality, and training, and iterate with them on the data, the model outputs, and the workflow until the solution works on the floor. You are comfortable rolling up your sleeves: pulling and checking data, testing outputs, running user sessions, and closing the loop between the site and the engineers.
# Why This Role Exists
Forward deployed teams are most powerful when paired with sharp opportunity selection and disciplined execution. This role closes that gap at this level by ensuring the engineers we deploy are working on the right things, and that what they build lands with the people at the site who will use it.
In this role you will be the person who:
• Drives opportunity discovery and value-case work on specific manufacturing engagements, supported by senior team members.
• Acts as a working partner to FDE pods on day-to-day scoping, delivery, and measurement.
• Works hands-on with site stakeholders, iterating on data, model outputs, and workflows...