Senior Ai Product Manager

GSK plc; Philadelphia (Philadelphia County); Hybride; USD 140 000 - 190 000; Plein temps

Résumé du poste

GSK plc in the United States offers a hybrid role for an AI Platform Product Manager to own AI/ML and data platform lifecycles, leading multi-year roadmaps for lakehouse, pipelines, governance, and GenAI initiatives. You will partner with senior engineers and business leaders to deliver ROI and regulatory-compliant value.

The position requires deep experience in data platforms and AI product management, strong strategic influence, and demonstrated leadership across cross-functional teams.

Responsabilités

• Own and drive a multi-year product vision and roadmap for data platform products (lakehouse, pipelines, governance) and AI/ML products (model lifecycle, RAG, GenAI, multi-agent systems).
• Partner with Director, Enterprise AI Platform and Principal Engineers to align strategy with data architecture and business priorities.
• Lead portfolio prioritisation across concurrent workstreams, balancing new capability development, technical debt, and regulatory needs.
• Assess emerging technologies (data mesh, GenAI, RAG, multi-agent orchestration) to inform platform investments.
• Engage Directors and VP-level stakeholders across R&D, Supply Chain, Commercial, IT to shape demand and ROI.
• Lead executive-level roadmap reviews, investment proposals, and architecture governance forums.
• Build strategic relationships with data domain leads, AI engineering leaders, and data scientists to forecast needs.
• Own end-to-end AI/ML product lifecycle: tooling, MLOps/LLMOps pipelines, GenAI apps, RAG systems, orchestration frameworks.
• Define AI-ready data product requirements: embeddings, feature stores, training data, evaluation frameworks.
• Champion Responsible AI practices: bias mitigation, explainability, compliance with NIST, GxP and EU AI Act.
• Own data platform products: ingestion pipelines, lakehouse layers, data cataloguing and lineage, data quality, self-service analytics.
• Lead analytics/BI product development: semantic layers, metrics catalogs, data marts powering Tableau/Power BI.
• Drive data governance strategy: metadata, data classification, access control, compliance tooling (GDPR, DPDP etc).
• Lead, mentor and develop PMs and BAs; manage backlog, epics, and acceptance criteria; drive agile ceremonies.
• Define and report on platform KPIs: adoption, AI quality, pipeline reliability, time-to-insight, delivery velocity.

Description du poste

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.

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.

Basic Qualification

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

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.

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.

Why GSK?

Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.

Why GSK?

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.

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.

If you require an accommodation or other assistance to apply for a job at GSK, please contact the appropriate Recruitment Staff by emailing us at - [e-mail]