Product Manager II

Role Summary

We are seeking an experienced Product Manager II responsible for designing and delivering the road map for target and patient discovery products to support GSK Research and Development. The role will drive an enterprise-level strategy for target and patient discovery solutions, ensuring scientists have access to best-in-class technology to improve research productivity and deliver new medicines for patients. The Product Management team partners with R&D stakeholders and Onyx leadership to develop a strategic roadmap for customer-facing aspects of Onyx, including data assets, ontology, Knowledge Graph / semantic search, data / computing / analysis platforms, and data-powered applications.

Responsibilities

• Contribute to Product Development & Adoption: participate in the full product lifecycle from development to launch and adoption, focusing on features within target and patient discovery solutions that enable identification and validation of drug targets and patient populations.
• Support GenAI Strategy: assist in integrating and enhancing GenAI capabilities within target and patient discovery tools, helping define and implement AI-powered functionalities.
• Deliver Collaboratively: partner with Onyx tech teams, R&D scientists, and leaders to deliver cloud-based products and solutions leveraging Generative AI and agentic capabilities.
• Product Strategy & Roadmap Contribution: help define and execute features within the target and patient discovery solutions roadmap, ensuring alignment with overall strategy.
• User Research & Feedback Analysis: conduct user interviews, gather feedback, and analyze data to inform product enhancements and iterative improvements.
• Product Feature Definition: translate user needs into clear requirements, user stories, and acceptance criteria for discrete features.
• Agile Development Engagement: participate in agile ceremonies, support backlog management and ensure understanding of product requirements.
• GenAI Feature Implementation Support: contribute to development of AI Agents leveraging LLMs and Generative AI; assist in design/testing of human-agent interactions; support model lifecycle and API/agent documentation; contribute to Model-In-The-Loop designs by gathering user feedback.
• Participate in technical product discussions with engineering leaders, translating scientific objectives into precise requirements for fine-tuning models, vector databases, and multi-agent architectures.
• Cross-Functional Coordination: align product strategies across DevOps/Infrastructure, data engineering, computing platforms, knowledge platforms, program management, and RD data leadership teams.
• Product Release Support: assist with launch activities, including documentation, training materials, and support resources for adoption.
• Performance Monitoring & Optimization: monitor metrics, gather user feedback on performance, and identify improvement areas.

Qualifications

• Required: PhD + 2 years, Masters + 2 years, or Bachelors + 4 years of education/experience.
• Required: 2+ years of product management experience shipping 0-to-1 software products powered by AI/GenAI, LLMs, or autonomous agents in a commercial or large-scale enterprise setting.
• Required: Experience executing product strategy for modern applications, including hands-on experience with AI system technologies such as vector databases, MLOps, retrieval-augmented generation, and model fine-tuning.
• Required: Technical experience with cloud-native architectures (e.g., AWS, GCP, Azure), API design, and infrastructure to serve and scale LLM-based applications.

• Preferred: Experience contributing to products involving AI agents, tool utilization (APIs, function calling), or development of conversational AI interfaces.
• Preferred: Hands-on software engineering or data science experience in an AI/GenAI-focused team prior to transitioning into product management.
• Preferred: Familiarity with transformer-based model architectures and trade-offs between proprietary, open-source, or fine-tuned models.
• Preferred: Experience with products enabling integration, visualization, and analysis of structured/unstructured biomedical data (genomics, proteomics, clinical data).
• Preferred: Foundational knowledge of bioinformatics, computational biology, or cheminformatics and interest in agentic AI impact on drug discovery.
• Preferred: Familiarity with Model Context Protocols (MCP) for LLM-powered agents, including prompt engineering concepts and context management.
• Preferred: Hands-on experience with product management tools (Confluence, Jira, Miro, Monday, Notion, etc.).
• Preferred: Previous experience in the life science industry or biopharma R&D is a plus.

Skills

• Strong ability to translate scientific needs into clear product requirements and roadmaps
• Experience working with AI/GenAI, LLMs, vector databases, and multi-agent systems
• Excellent collaboration across cross-functional teams and technical leadership
• Proficiency with agile methodologies and product lifecycle management