Description
Job descriptionThe Onyx Research Data Tech organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines. We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:
Building a next-generation data experience for GSK's scientists, engineers, and decision-makers, increasing productivity and reducing time spent on "data mechanics"
Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent
Aggressively engineering our data at scale to unlock the value of our combined data assets and predictions in real-time
Onyx Product Management is at the heart of our mission, ensuring that everything from our infrastructure, to platforms, to end-user facing data assets and environments is designed to maximize our impact on R&D. The Product Management team partners with R&D stakeholders and Onyx leadership to develop a strategic roadmap for all customer-facing aspects of Onyx, including data assets, ontology, Knowledge Graph / semantic search, data / computing / analysis platforms, and data-powered applications.
We are seeking an experienced Senior Product Manager who will be accountable for designing and delivering the road map for molecule design products to support GSK Research and Development. This role will be pivotal in ensuring a cohesive enterprise level strategy towards molecule design solutions and will ensure our scientists have access to best-in-in-class technology products to improve research productivity and ultimately deliver new medicines for our patients.
In this role you will:
Own and lead the product roadmap, product development, launch and adoption of novel molecule design solutions to benefit the scientific community at GSK across multiple departments
Play a key role in defining the strategic direction for molecule design tools with GenAI capabilities at the core
Partner closely with the wider Onyx tech team, as well as R&D scientists and leaders, to deliver industry-leading cloud-based products and solutions with GenAI and agentic capabilities.
Key Responsibilities:
Product Strategy and Roadmap: Develop and execute a comprehensive product strategy and roadmap for molecule design solutions and tools, aligned with the Onyx's overall product vision and objectives.
Customer Understanding: Conduct in-depth customer research, gather customer insights, and engage with customers regularly to understand emerging requirements.
Product Planning and Definition: Collaborate with stakeholders to define product requirements, features, and specifications based on customer feedback, product vision, and business goals.
Agile Product Development: Work closely with portfolio and engineering teams in an agile environment to ensure successful and timely delivery of product releases, including prioritization, sprint planning, and backlog management.
GenAI Product and Capability Upgrade:
Spearhead the development of a new class of AI Agents, powered by LLMs and Generative AI, designed to autonomously execute complex scientific research tasks like hypothesis generation, experimental design, and data interpretation.
Design and productize the human-agent interaction layer, moving beyond traditional UIs to create conversational and goal-driven interfaces that allow scientists to delegate multi-step tasks and interpret the outputs of autonomous GenAI systems.
Own the product lifecycle for models and agents, leading the strategy for data acquisition, model fine-tuning, and the development of APIs/agents that allow them to be leveraged as "tools" by other agents and systems.
Model-In-The-Loop Design: Structuring products so that R&D users can easily challenge, verify, and provide feedback to improve the agentic tools and underlying models (human-guided iteration). Demonstrate Human + AI collaboration with minimum friction to drive user adoption.
Lead highly technical product discussions with engineering leaders, translating ambiguous scientific objectives into precise requirements for fine-tuning foundational models, vector databases, and multi-agent system architectures.
Cross-Functional Collaboration: Collaborate with both tech and RD teams, including DevOps& Infrastructure, data engineering, computing platform engineering, data & knowledge platform engineering, program management teams and RD data leadership teams, to align product strategies, gather input, and drive successful implementation plans.
Product Launch and Adoption: Lead product launches, ensuring effective communication, training, and support materials to drive successful product adoption and customer satisfaction.
Product Performance and Optimization: Continuously monitor product performance, collect and analyze data, and drive iterative improvements to enhance product usability, performance, and customer experience.
Why you?
Qualifications & Skills:
We are looking for professionals with these required skills to achieve our goals:
Bachelors degree in Bioinformatics, Computational Biology, cheminformatics, AI/ML, Computer Science, Software Engineering, or related discipline.
Significant experience in product management with a proven track record of shipping 0-to-1 software products powered by AI/GenAI, LLMs, or autonomous agents in a commercial or large-scale enterprise setting.
Demonstrated experience defining product strategy for modern applications, including hands-on experience with technologies core to AI systems such as vector databases, MLOps, retrieval-augmented generation, and model fine-tuning.
Direct product management experience designing and launching AI agents that can utilize tools (APIs, function calling) to perform complex, multi-step actions and reason about their environment.
Deep technical fluency with cloud-native architectures (e.g., AWS, GCP, Azure), API design, and the infrastructure required to serve and scale LLM-based applications
Preferred Qualifications & Skills:
If you have the following characteristics, it would be a plus:
Master's degree or PhD in Bioinformatics, Computational Biology, Computational Chemistry, Data Science, Computer Science/Software Engineering, Cloud Computing or related discipline.
Hands-on software engineering or data science experience in a GenAI-focused team prior to transitioning into product management.
Familiarity with the architecture of modern transformer-based models and the strategic product trade-offs between using proprietary models (e.g., GPT-4, Claude), open-source models (e.g., Llama, Mistral), and fine-tuning custom models.
Experience building products that manage or interpret complex, unstructured biomedical data
Extensive knowledge of bioinformatics, computational biology, or cheminformatics, and a strong vision for how agentic AI can revolutionize the drug discovery process.
Extensive product experience designing, optimizing, and implementing Model Context Protocols (MCP) for LLM-powered agents, including advanced strategies for prompt engineering, context window management, memory architectures (e.g., short-term, long-term memory), and ensuring model coherence over extended multi-turn interactions.
Hands-on experience with product management tools such as Confluence, Jira, Miro, Monday, Notion, etc.
Previous experience in life science industry or biopharma R&D is a plus.
Closing Date for Applications: Tuesday 6th January 2026 (COB)
Please note: As we approach the holiday season, our recruitment team and hiring managers will have limited availability between now and early January. We encourage you to apply and will review all applications, however response times may be longer than usual, and interviews may be scheduled after the New Year. We appreciate your understanding and look forward to connecting soon!
Please take a copy of the Job Description, as this will not be available post closure of the advert.
When applying for this role, please use the 'cover letter' of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above. The information that you have provided in your cover letter and CV will be used to assess your application.
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