Product Manager II
The 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 Product Manager II who will be accountable for designing and delivering the roadmap for target and patient discovery products to support GSK Research and Development. This role will be pivotal in ensuring a cohesive enterprise level strategy towards target and patient discovery 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 :
Contribute to Product Development & Adoption : Actively contribute to the full product lifecycle, from development to launch and adoption, focusing on specific features and components within novel target and patient discovery solutions that enable identification and validation of drug targets and patient populations, benefitting the scientific community at GSK.
Support GenAI Strategy : Support the strategic integration and enhancement of GenAI capabilities within target and patient discovery tools, helping to define and implement next-generation AI-powered functionalities.
Deliver Collaboratively : Partner closely with Onyx tech teams, R&D scientists, and leaders to facilitate the delivery of impactful cloud-based products and solutions that leverage Generative AI and agentic capabilities.
Key Responsibilities Include :
- Product Strategy & Roadmap Contribution : Contribute to the definition and execution of specific features and components within the target and patient discovery solutions roadmap, ensuring alignment with the overall product strategy.
- User Research & Feedback Analysis : Collaborate with subject matter experts, conduct user interviews, gather feedback, and analyze user data to inform the definition of product enhancements and identify opportunities for iterative improvements in target and patient discovery tools.
- Product Feature Definition : Work closely with Senior Product Managers and engineering teams to translate user needs into clear, well-defined product requirements, user stories, and acceptance criteria for discrete features.
- Agile Development Engagement : Actively participate in agile ceremonies (e.g., sprint planning, backlog refinement, stand-ups) with engineering teams, ensuring product requirements are understood and supporting effective backlog management.
- GenAI Feature Implementation Support :
Contribute to the development and implementation of specific features within AI Agents that leverage LLMs and Generative AI to automate well-defined parts of scientific research tasks.
Assist in the design and testing of human-agent interaction components, focusing on specific conversational flows or user interface elements to enhance usability.Support the product lifecycle for individual models or agents by assisting with data gathering, testing of fine-tuned models, and developing documentation for APIs / agents.Support the implementation of Model-In-The-Loop designs by gathering R&D user feedback and contributing to theTechnical Product Discussions : Participate in and contribute to 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 Coordination : Coordinate 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 ensure clear communication and smooth execution.Product Release Support : Assist with product launch activities for new features, including preparing documentation, training materials, and support resources to ensure successful adoption.Performance Monitoring & Optimization : Monitor key metrics for specific product features, gather user feedback on performance, and identify potential areas for improvement.Why You?
Basic Qualifications :
PhD + 2 years, Masters + 2 years, or Bachelors + 4 years2+ years of 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.Experience in executing 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.Technical knowledge with cloud-native architectures (e.g., AWS, GCP, Azure), API design, and the infrastructure required to serve and scale LLM-based applications.Preferred Qualifications :
Experience contributing to products that involve AI agents, their tool utilization (APIs, function calling), or the development of conversational AI interfaces.Hands-on software engineering or data science experience in an AI / GenAI-focused team prior to transitioning into product management.Familiarity with the architecture of modern transformer-based models and an understanding of the strategic trade-offs when selecting between proprietary, open-source, or fine-tuned custom models.Experience contributing to products that facilitate integration, visualization, and analysis of structured and unstructured biomedical data (e.g., genomics, proteomics, clinical data).Foundational knowledge of bioinformatics, computational biology, or cheminformatics, and an interest in how agentic AI can impact drug discovery.Familiarity with Model Context Protocols (MCP) for LLM-powered agents, including basic concepts of prompt engineering, context window management, and maintaining model coherence in multi-turn interactions.Hands-on experience with product management tools such as Confluence, Jira, Miro, Monday, Notion, etc.Previous experience in the life science industry or biopharma R&D is a plus.