Product Manager II

Role Summary

The Onyx Research Data Tech organization is delivering a strategic, enterprise‑level set of data, AI/ML, and analysis capabilities to support GSK R&D. We are seeking an experienced Product Manager II who will design and deliver the road map for target and patient discovery products, ensuring scientists have access to best‑in‑class technology to improve research productivity and deliver new medicines.

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/validation of drug targets and patient populations.
• Support GenAI Strategy: help define and implement next‑generation AI‑powered functionalities within target and patient discovery tools.
• Deliver Collaboratively: partner with Onyx tech teams, R&D scientists, and leaders to deliver cloud‑based products and solutions that leverage Generative AI.
• Product Strategy & Roadmap Contribution: contribute to the definition and execution of features within the target and patient discovery roadmap, aligned with the overall product 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 with engineering teams to ensure requirements are understood and backlog management is effective.
• GenAI Feature Implementation Support: contribute to features within AI Agents that leverage LLMs/Generative AI, support human‑agent interaction design, assist with data gathering, model fine‑tuning, and API/agent documentation; support Model‑In‑The‑Loop designs by gathering user feedback.
• Technical Product Discussions: translate scientific objectives into precise requirements for fine‑tuning models, vector databases, and multi‑agent architectures.
• Cross‑Functional Coordination: coordinate with DevOps, data engineering, computing platform, knowledge platform engineering, program management, and RD data leadership to align strategies and ensure smooth execution.
• Product Release Support: assist with launch activities, including documentation, training materials, and support resources.
• Performance Monitoring & Optimization: monitor metrics, gather feedback, and identify areas for improvement.

Qualifications

• Required: PhD + 2 years, Masters + 2 years, or Bachelors + 4 years of 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 with hands‑on experience in AI system technologies such as vector databases, MLOps, retrieval‑augmented generation, and model fine‑tuning.
• Required: Technical experience with cloud‑native architectures (AWS, GCP, Azure), API design, and infrastructure to serve and scale LLM‑based applications.
• Preferred: Experience contributing to products involving AI agents, tool utilization, or 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 model architectures and trade‑offs among proprietary, open‑source, or fine‑tuned models; experience with integrating/visualizing biomedical data.
• Preferred: Foundational knowledge in bioinformatics, computational biology, or cheminformatics; interest in agentic AI for drug discovery.
• Preferred: Familiarity with Model Context Protocols (MCP) for LLM‑powered agents and prompt engineering concepts.
• Preferred: Experience with product management tools (Confluence, Jira, Miro, Monday, Notion, etc.).
• Preferred: Life sciences or biopharma R&D experience.

Skills

• Product management for AI/GenAI powered platforms
• GenAI/LLM technology, AI agents, conversational interfaces
• Cloud architecture, API design, and scalable infrastructure
• User research, requirements definition, and agile delivery
• Cross‑functional collaboration across R&D, engineering, and operations