The posting
GSK is one of the world’s foremost pharmaceutical and healthcare companies and we are proud to be leading a healthcare revolution.
By disrupting our approaches to R&D and commercial business processes, AI and agents are allowing us to integrate, simplify and unlock all our data to drive innovation, decision making and enable our transformation in servicing our patients, healthcare professionals and consumers.
You will set multi-year product direction, shape platform strategy alongside the Director and Principal Engineers, lead a team of PMs, and serve as the senior product voice to Director and VP-level stakeholders. This is a high-influence, high-accountability role at the convergence of enterprise data and cutting-edge AI.
KEY RESPONSIBILITIES
Product Vision & Portfolio Strategy
- Own and drive a compelling multi-year product vision and roadmap spanning data platform products (lakehouse, pipelines, governance, BI) and AI/ML products (model lifecycle, RAG, GenAI, multi-agent systems).
- Partner with the Director, Enterprise AI Platform and Principal Engineers to align product strategy with enterprise data architecture and GSK’s business priorities.
- Lead portfolio prioritisation across concurrent workstreams, balancing new capability development, technical debt, and regulatory compliance needs.
- Assess emerging technologies (data mesh, GenAI, advanced RAG, multi-agent orchestration) to inform platform investment decisions.
Stakeholder Leadership
- Engage Director and VP-level stakeholders across R&D, Supply Chain, Commercial, and IT to shape demand, align priorities, and communicate platform value and ROI.
- Lead executive-level roadmap reviews, investment proposals, and architecture governance forums representing the product organisation.
- Build strategic relationships with data domain leads, AI engineering leaders, and data scientists to understand long-term needs.
AI/ML Product Management
- Own end-to-end AI/ML product lifecycle: model development tooling, MLOps and LLMOps pipelines, GenAI applications, RAG systems, and multi-agent orchestration frameworks.
- Define AI-ready data product requirements: embeddings, feature stores, versioned training data, and evaluation frameworks (hallucination benchmarks, responsible AI checkpoints).
- Champion Responsible AI (RAI) practices: ethical model development, bias mitigation, explainability, and compliance with NIST, GxP, and EU AI Act guidance.
Data & Analytics Product Management
- Own data platform products: ingestion pipelines, lakehouse layers (Delta Lake, Iceberg), data cataloguing and lineage (Purview, Unity Catalog), data quality, and self-service analytics foundations.
- Lead analytics and BI product development: semantic layers, metrics catalogues, and data marts powering Tableau, Power BI, and programmatic analytics at scale.
- Drive data governance product strategy: metadata management, data classification, access control, and compliance tooling (GDPR, GxP, DPDP Act India).
Delivery & Team Leadership
- Lead, mentor, and develop a team of Product Managers and Business Analysts within the platform product organisation.
- Own backlog health across multiple engineering squads; write high-quality epics, user stories, and acceptance criteria; drive agile ceremonies with engineering leadership.
- Define and report on platform KPIs covering adoption, AI quality, pipeline reliability, time-to-insight, delivery velocity, and stakeholder satisfaction.
Why You? Basic Qualification We are seeking professionals with the following required skills and qualifications to help us achieve our goals:
- Bachelor’s or Master’s in Computer Science, Data Engineering, Business Analytics, Information Systems, or a related field.
- 8+ years of product management experience, with at least 4 years on data platforms, AI/ML products, or enterprise analytics infrastructure.
- Experience owning a multi-product portfolio and leading other PMs or BAs
- Exceptional product sense: portfolio-level prioritisation, high-stakes trade-off decisions, and OKR-driven roadmapping across multiple engineering squads.
- Mastery of agile delivery and tooling (Jira, Confluence, Productboard, Miro); produces executive-grade artefacts: strategy docs, business cases, roadmaps, and PRDs
- Experience with lakehouse architecture, data mesh, batch and streaming pipelines, data cataloguing, lineage, data quality, and self-service analytics.
- Experience with Azure Synapse, Databricks, Delta Lake, and dbt, including technical architecture conversations with Principal Engineers. ·
- Experience with BI tooling (Tableau, Power BI, semantic layers) and with reading and reasoning about SQL and Python
- Experience with the end-to-end ML lifecycle, MLOps, LLMOps, RAG architectures, vector databases, and multi-agent systems.
- Experience managing GenAI or LLM-powered products in production: prompt engineering, model evaluation, hallucination mitigation, and responsible AI integration.
- Experience with executive communication, including board-ready decks, investment proposals, and compelling narratives for technical and business audiences.
- Experience influencing at Director/VP level and working across distributed, matrixed organisations
Preferred Qualification If you have the following characteristics, it would be a plus:
- Advanced AI product experience: fine-tuning pipelines, synthetic data, RLHF-powered products
- Data mesh: domain data product ownership, data contracts, federated governance
- GxP, EU AI Act, FDA AI guidance, GDPR, or DPDP Act India regulatory experience
- Pharma, life sciences, or regulated healthcare industry background
- Open-source AI/ML or data community involvement
- Formal PM certifications: CSPO, AIPMM, SAFe, or equivalent
- Experience working with SAP landscapes, including SAP Business Data Cloud (BDC) and SAP data sources feeding enterprise data platforms
- Exposure to ECC-to-S/4HANA transformation programmes, ideally having used AI or GenAI to augment and accelerate migration, data readiness, or process transformation
Work Arrangement This role is offered as a hybrid position in the United States. You will be on-site part of the week and work remotely the remainder. Strong collaboration across teams and time zones will be required.
#LI-GSK
#AGTech
Skills
AI Platforms, Change Management, Data Analysis, Feature Prioritization, Machine Learning Model Management, ML Platforms, Model Evaluation, Performance Analysis, Product Delivery, Product Design, Product Lifecycle Management (PLM), Product Roadmapping, Roadmap Development, Statistical Analysis, User Needs Analysis
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
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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.
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