Principal (Senior Director), Commercial Enterprise AI Product Mgmt. - Knowledge Foundation and Insights Acceleration

GSK • Philadelphia, PA

3d • $195,525 - $325,875

About The Position

GSK's Enterprise AI team translates AI into measurable impact across major business groups. This senior individual-contributor role sets the strategy for a portfolio of AI solutions that accelerate insights globally, from primary and secondary market research and competitive-intelligence knowledge bases to agentic tools that bring insights to decision-makers. The role identifies and prioritizes high-value opportunities, shapes the work of forward-deployed teams, and ensures engineering capacity is focused on the most impactful initiatives. It does not manage engineers; instead, it defines what they build, where they focus, and how outcomes are measured.

The position owns opportunity selection and portfolio strategy for AI across the insights-acceleration lifecycle. It frames ambiguous business problems, develops business cases and prototypes, secures executive alignment and sponsorship, and partners with engineering teams from engagement design through delivery and scaling. The role also establishes value-realization measures, identifies opportunities for reusable platform capabilities, and communicates AI impact in terms relevant to patients, science, and business outcomes.

Requirements

• 15 or more years of professional experience across some combination of pharma/life sciences, AI/ML product strategy, and product management or strategy roles in technology-led organizations.
• Track record of taking at least one technology or AI initiative from problem framing through executive funding and into delivery.
• Hands-on work with data foundations for pharma market research and competitive intelligence, including taxonomy, ontology, metadata management, common data model design, or KPI frameworks, applied to third-party datasets such as IQVIA or Komodo.
• Track record of building or specifying knowledge graphs and conversational or agentic AI interfaces that deliver insights to business decision-makers.
• Hands-on experience with modern AI/ML concepts, including LLMs, agentic systems, digital workers, the ML lifecycle, and data and evaluation patterns, demonstrated through prototyping.
• Experience operating as an individual contributor without direct reports and influencing engineering and business teams through frameworks and documented decision criteria.
• Prior responsibility for product management or product strategy, including opportunity sizing, roadmap development, prototyping, and stakeholder alignment.
• Experience with the commercial analytics data landscape and the technology capabilities used to operationalize insights at scale.
• Direct involvement in analyzing intelligence sources and delivering insights used in business planning or portfolio decisions.
• Track record of building and maintaining knowledge bases spanning multiple commercial domains.
• Prior responsibility for aggregating regional market intelligence into national or global insights used for decision-making.

Nice To Haves

• Experience in a forward-deployed engineering, applied AI, or AI lab/COE role at a pharma, healthcare, or comparable regulated enterprise.
• Background in management consulting, value engineering, or corporate strategy combined with hands-on technology experience.
• Experience navigating GxP, regulatory, and data-governance requirements in pharma AI deployments.
• Experience with data foundation and knowledge platforms used in pharma insights, such as MDM/data fabric tools (Reltio, Informatica, Palantir Foundry), graph databases (Neo4j, Amazon Neptune), or vector search/RAG infrastructure.

Responsibilities

• Identify and prioritize high-value AI opportunities across the insights-acceleration lifecycle, including market research, competitive intelligence, third-party data foundations, knowledge graphs, and agentic interfaces.
• Build a global portfolio of AI products ranked by impact, feasibility, and time-to-value.
• Develop rigorous business cases and quantify value, including cycle time saved, decisions accelerated, revenue uplift, cost avoided, and scientific productivity gained.
• Develop expertise in organizing market, competitive, and HCP/patient data for compliant and secure insights generation.
• Maintain a current portfolio view of in-flight, queued, and de-prioritized opportunities, documenting the rationale for decisions.
• Create decision frameworks, define success metrics, analyze competing needs, and recommend how engineering resources should be allocated.
• Decline opportunities that are unlikely to produce scalable outcomes, using evidence to protect engineering focus.
• Partner with forward-deployed, full-stack, and data engineering leads to translate business problems into clear problem statements, prototypes, metrics, and decision frameworks.
• Shape engagements end-to-end by defining scope, success criteria, exit conditions, and scaling pathways before launch, and staying involved during execution.
• Identify opportunities to reuse solutions or leverage platforms and work with engineering teams to develop reusable capabilities.
• Design the division of work between digital workers, engineers, and business users, including evaluation and oversight approaches.
• Lead executive discussions that turn broad ambitions into concrete, fundable AI engagements.
• Build sponsor coalitions and secure executive support, data access, and change-management commitment for deployments.
• Communicate AI impact to executive leadership and the board, connecting outcomes to patients, science, and shareholder value.
• Establish the value-realization framework used to measure impact across Enterprise AI deployments.
• Conduct post-mortems and incorporate lessons into opportunity selection and engagement design.
• Continuously refine the investment thesis for where AI should and should not be applied at GSK.

Benefits

• Annual bonus
• Eligibility to participate in a share-based long-term incentive program, dependent on role level
• Health care and other insurance benefits for employees and family
• Retirement benefits
• Paid holidays
• Vacation
• Paid caregiver, parental, and medical leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed