Senior Product Manager

Senior Product Manager 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 Senior Product Manager who will be accountable for designing and delivering the road map 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: Drive Product Development & Adoption: Own and lead the product roadmap, product development, launch and adoption of novel target and patient discovery solutions that enable identification and validation of drug targets and patient populations, benefitting the scientific community at GSK across multiple departments. Shape GenAI Strategy: Play a key role in defining the strategic direction for target and patient discovery tools with GenAI capabilities at the core. Deliver Collaboratively: 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 Include Product Strategy and Roadmap: Develop and execute a comprehensive product strategy and roadmap for target and patient discovery 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. 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 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: Define and continuously monitor product performance metrics, collect and analyze data, and drive iterative improvements to enhance product usability, performance, and customer experience. Why You? Basic Qualifications PhD + 2 years, Masters + 4 years, or Bachelors + 6 years 4+ 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 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. 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 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. 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 facilitate integration, visualization, and analysis of structured and unstructured biomedical data (e.g., genomics, proteomics, clinical 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.

Created: 2026-03-04