Senior, AI Product Manager (Tech Transfer & Strategy)

Description

Senior AI Product Manager (Tech Transfer and Strategy) in the company's Enterprise AI team, the group that applies artificial intelligence across the business.

Forward deployed and full-stack engineers work alongside scientific, clinical and business teams to build AI products that people actually use, rather than pilots that stall. The team moves quickly, ships to production and tracks results that affect patients.

The company is a global biopharma company aiming to positively affect the health of 2.5 billion people by the end of the decade. It focuses on respiratory, immunology and inflammation, oncology, HIV, and infectious diseases.

The role sits in Chemical Manufacturing and Control (CMC), the function that turns a validated molecule into a reliably made, quality-assured medicine. Its current goal is to double New Product Introductions (NPIs).

You will help decide where AI can create the most value across the company's manufacturing sites worldwide and keep the team on the highest-impact work. You will rank opportunities with business stakeholders by feasibility and value.

The team values people who are practical, inclusive and open to feedback. They communicate in the active voice, keep messages simple, and want to build product and security skills.

Responsibilities

• Take complex business problems, structure them, size their value and prototype them hands-on, so a forward deployed engineer can build against the result.
• Run the day-to-day tech transfer work with sites and Contract Manufacturing Organizations (CMOs), and redesign processes in detail.
• Shape the NPI launch strategy toward one-click deployment of a new line and product. This covers site impact assessment, capacity management, digital twins, scenario planning and virtual commissioning of lines.
• Define the target architecture and own the tech transfer package, including its content, structure, data and knowledge, and how it is generated, validated and kept current in an AI-native way.
• Drive an AI-native, end-to-end redesign of the tech transfer process. Decide which steps agents automate, which keep humans in the loop, and how agents connect with site systems such as Manufacturing Execution Systems (MES).
• Lead recipe building for new products. Turn process knowledge and the tech transfer package into structured, executable MES recipes, such as master and control recipes in ISA-88 style, and use agents to draft, check and adapt them to each site.
• Surface and size AI opportunities across your engagements and adjacent business units. Write one-page opportunity briefs that are easy to compare and prioritise.
• Build value cases with finance-grade reasoning on cycle time saved, faster decisions, revenue uplift or cost avoided.
• Build hands-on domain knowledge of the workflows, data, decisions and people in your engagement areas.
• Recommend what to start, continue or stop, based on evidence rather than enthusiasm. Sequence work for impact, deciding what is in scope this sprint, what is next and what is out.
• Act as the day-to-day strategic partner to FDE pods. Turn business ambiguity into problem statements, success metrics and decision frameworks that engineers can act on.
• Run each engagement end to end, covering scope, success criteria, exit conditions and scaling paths, and revisit them as needed.
• Spot reusable patterns that should become platform capability rather than point solutions.
• Run working sessions with Director-level business and scientific stakeholders that end in decisions. Keep sponsors informed with concise updates, honest risk calls and clear asks.
• Track value realised on each engagement against the case written up front, and capture lessons to shape how the next engagement is scoped.

Requirements

• Strong, progressive experience in pharma or life sciences, AI or ML product, product management, or strategy in technology-led organisations, in any combination.
• A record of turning complex, ambiguous business problems into structured, sized opportunities with business cases that hold up.
• Working knowledge of GSC and technology transfer, including sites, MSAT and supply chain, and how decisions really get made on the ground.
• Proven day-to-day work with sites and operational teams, building trust and turning their pain points into AI-shaped opportunities.
• Practical technical fluency in modern AI and ML, enough to design realistic engagements with engineers and avoid hype-driven choices.
• Proven experience redesigning business processes step by step in an AI-native way, reaching 10x transformation.
• Strong individual contribution. You produce quality artefacts, not status updates.
• Grounding in product management discovery and value framing.
• Skills across AI platforms, ML platforms and model management and evaluation, product roadmapping and feature prioritisation, statistical and performance analysis, user needs analysis, change management and product lifecycle management.
• Preferred: experience working with site MSAT, technology transfer leads or manufacturing operations teams.
• Preferred: experience with MES and adjacent systems such as LIMS, ERP, QMS, historians and electronic batch records, and an understanding of how their data feeds tech transfer and launch readiness.
• Preferred: experience building and authoring manufacturing recipes in MES and automation platforms such as PAS-X, Syncade and DeltaV, and managing recipe changes across sites.
• Preferred: familiarity with DTLS and similar digital twin, process modelling and simulation tools, and how they inform recipe design, scale-up and tech transfer decisions.
• Preferred: experience with data analytics, data science or process science teams to deliver a 10x change in modelling, optimisation and simulation.
• Preferred: experience in regulated industries such as pharma, healthcare or financial services, with familiarity with GxP and data-governance constraints.
• Preferred: prior experience as an AI product manager at an AI-native company such as Anthropic, Palantir or OpenAI, or at a hyperscaler.
• Bachelor's degree in Computer Science, Software Engineering or equivalent practical experience.
• Advantageous: a master's degree in Computer Science or a related field.

Conditions

UK-based hybrid role with a minimum of 2/3 days a week onsite. Fully remote working is not available.

Based at HQ in Central London or Stevenage. The role can temporarily be based in Stevenage.

The company plans to move its offices to Ware, UK, and the role will then move to Ware on timelines the company sets. The move is currently proposed to take effect by early 2029.

The team works with an agile culture, and flexibility can be discussed with the hiring team.

Closing date: 13th November 2026.

The company welcomes candidates from all backgrounds, and US licensed healthcare professionals may have interview expenses reported under US transparency rules.

Benefits

• Access to learning and development to build technical and leadership skills.
• A supportive team that values clear communication and practical problem solving.
• Work that supports technology used across the company and helps improve healthcare outcomes.