The Association of Technology, Management and Applied Engineering
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. Responsibilities 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 molecule design solutions for the scientific community at GSK. Support GenAI Strategy: Support the strategic integration and enhancement of GenAI capabilities within molecule design tools, helping to define and implement next generation AI powered functionalities. Collaborative Delivery: 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. GenAI Feature Implementation Support: Contribute to the development and implementation of specific features within AI Agents, leveraging 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 the process. Participate in 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 tech and R&D teams, including DevOps & Infrastructure, data engineering, computing platform engineering, data & knowledge platform engineering, program management teams and R&D data leadership teams, to align product strategies, gather input, ensuring 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. Qualifications Bachelor's degree in Bioinformatics, Computational Biology, cheminformatics, AI/ML, Computer Science, Software Engineering, or related discipline. 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 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. Demonstrated 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 Master's degree or PhD in Bioinformatics, Computational Biology, Computational Chemistry, Data Science, Computer Science/Software Engineering, or related discipline. Experience contributing to products that involve AI agents, their tool utilisation (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 manage or interpret complex, unstructured biomedical data. 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. Foundational knowledge of bioinformatics, computational biology, or cheminformatics, and an interest in how agentic AI can impact drug discovery. 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. 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 we will review all applications; however response times may be longer than usual, and interviews may be scheduled after the New Year. GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
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. Responsibilities 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 molecule design solutions for the scientific community at GSK. Support GenAI Strategy: Support the strategic integration and enhancement of GenAI capabilities within molecule design tools, helping to define and implement next generation AI powered functionalities. Collaborative Delivery: 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. GenAI Feature Implementation Support: Contribute to the development and implementation of specific features within AI Agents, leveraging 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 the process. Participate in 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 tech and R&D teams, including DevOps & Infrastructure, data engineering, computing platform engineering, data & knowledge platform engineering, program management teams and R&D data leadership teams, to align product strategies, gather input, ensuring 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. Qualifications Bachelor's degree in Bioinformatics, Computational Biology, cheminformatics, AI/ML, Computer Science, Software Engineering, or related discipline. 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 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. Demonstrated 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 Master's degree or PhD in Bioinformatics, Computational Biology, Computational Chemistry, Data Science, Computer Science/Software Engineering, or related discipline. Experience contributing to products that involve AI agents, their tool utilisation (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 manage or interpret complex, unstructured biomedical data. 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. Foundational knowledge of bioinformatics, computational biology, or cheminformatics, and an interest in how agentic AI can impact drug discovery. 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. 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 we will review all applications; however response times may be longer than usual, and interviews may be scheduled after the New Year. GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.