Senior, AI Product Manager (Process Development Science)

Description

The company's Enterprise AI team builds AI products with forward deployed engineers, full-stack engineers, and scientific, clinical and business teams, aiming for tools that people use in production.

The company is a global biopharma business focused on respiratory, immunology and inflammation, oncology, HIV, and infectious diseases.

This Senior AI Product Manager role sits in Chemical Manufacturing & Control (CMC), the function that moves a validated molecule into reliable, quality-assured manufacturing. CMC's current goal is to double New Product Introductions (NPIs).

You will shape where AI improves process development worldwide, find the highest-value opportunities, and set priorities with business stakeholders based on feasibility and value. You will turn complex problems into structured briefs, prototype them yourself, and hand them to a forward deployed engineer (FDE) to build.

You will run day-to-day AI work in process development science for R&D. This includes redesigning platform thinking for oligonucleotides (oligos), antibody-drug conjugates (ADCs) and monoclonal antibodies, and supporting self-driving labs that automate the physical lab. The aim is a 10x change in modeling, optimization, agentic workflows, document authoring and physical AI for simulation, working with the process science data analytics team and the R&D Tech teams.

Responsibilities

• Find and size AI opportunities across your engagements and neighbouring business units, and write one-page briefs that are easy to compare and rank.
• Build value cases with finance-grade reasoning for cycle time saved, faster decisions, revenue uplift or cost avoided.
• Build working knowledge of your engagement areas, including workflows, data, decisions and the people who own them.
• Recommend what to start, continue or stop, based on evidence.
• Sequence work by impact and help engineering leads decide what is in scope this sprint, what comes next, and what is out.
• Act as the daily strategic partner to FDE pods. Turn vague business needs into clear problem statements, success measures and decision frameworks.
• Own each engagement from end to end: scope, success criteria, exit conditions and routes to scale, agreed and revisited as needed.
• Identify reusable patterns that should become shared platform capability rather than one-off solutions.
• Run working sessions with Director-level business and scientific stakeholders that end in decisions, not just notes.
• Keep sponsors informed with short updates, candid risk calls and clear requests.
• Track value delivered on each engagement against the case written at the start.
• Record lessons carefully and use them to scope the next engagement.

Requirements

• Required: strong, progressive experience in pharma or life sciences, AI or ML product, product management, or strategy in technology-led organisations.
• Required: a record of turning complex, unclear business problems into structured, sized opportunities with solid business cases.
• Required: working knowledge of process modeling, manufacturing and laboratory content in R&D, including how decisions really get made on the ground.
• Required: proven experience redesigning platform strategy for drug modalities such as oligonucleotides, ADCs and monoclonal antibodies.
• Required: proven experience finding opportunities in self-driving labs, in silico modeling and platform fitness, and shaping them into a 10x change.
• Required: proven experience designing strategy for multi-initiative workstreams, including finding opportunities in the business, sizing value and owning outcome-based delivery.
• Required: enough technical fluency in modern AI and ML to design realistic engagements with engineers and avoid hype-driven choices.
• Required: strong individual contributor habits, producing quality artefacts rather than status updates.
• Optional: experience in process development or manufacturing for oligonucleotides, ADCs or monoclonal antibodies.
• Optional: experience with self-driving labs and lab automation of the physical space, in silico modeling, or platform fitness products and programs.
• Optional: experience working with data analytics, data science or process science teams to drive a 10x change in modeling, optimization and simulation.
• Optional: experience in regulated industries such as pharma, healthcare or financial services, with familiarity with GxP and data-governance constraints.
• Education: a bachelor's degree in Computer Science, Software Engineering or equivalent practical experience. A master's degree in Computer Science or a related field is advantageous.
• Skills listed for this role: 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.
• You are practical, inclusive and open to feedback. You understand technology, care about users, communicate simply in active voice, support colleagues, and help teams decide based on evidence. You want to build your product and security skills.

Conditions

This is a UK-based hybrid role with at least 2 to 3 days a week onsite. Fully remote working is not offered.

Base is HQ in Central London or Stevenage. The role may temporarily sit in Stevenage, but the company plans to move its offices to Ware, UK, and the role will then move to Ware on a timeline the company will set. The move is currently proposed for early 2029.

The company works to an agile working culture for all roles. If flexibility matters to you, ask the hiring team what is available.

The closing date is 13th November 2026.

Tags: AGTech, LI-Hybrid.

The company welcomes applicants from all backgrounds, including groups underrepresented in technology, science and pharma.

Benefits

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