Senior Ai Product Manager

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.

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