Principal, Senior Director – Commercial Enterprise AI Product Management, Field Force Effectiveness

GSK

. Hunt for high-value AI opportunities across the field force effectiveness lifecycle and develop a global portfolio of AI products ranked by impact, feasibility, and time-to-value .

Posted 10/19/2026full-timeUnited StatesSenior💰 $177,750 - $296,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in AI/ML product strategy and management within the pharma/life sciences sector, with a strong focus on opportunity identification, business case development, and stakeholder engagement. Proficient in navigating regulatory requirements and leveraging field analytics to drive impactful AI initiatives.

Highest-signal resume keywords

AI/ML Product StrategyPharma Field Force OperationsOpportunity SizingStakeholder AlignmentGxP Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Business Case DevelopmentOpportunity IdentificationPrototypingData Evaluation PatternsField AnalyticsKPI AutomationDigital Worker OwnershipSuccess Metrics DefinitionDecision FrameworksAI Impact Communication

Soft Skills

Influencing Engineering TeamsChange Management CommitmentCoalition BuildingCommunication with Senior LeadersAnalytical Thinking

Tools & Technologies

Veeva CRMSalesforceIQVIA DataOmnichannel Engagement PlatformsField Deployment Processes

Industry Keywords

PharmaLife SciencesRegulatory RequirementsData GovernanceManagement Consulting

Tech Stack

Tools & technologies

Vault

About the role

Key responsibilities & impact

Hunt for high-value AI opportunities across the field force effectiveness lifecycle and develop a global portfolio of AI products ranked by impact, feasibility, and time-to-value
Quantify value by building business cases covering cycle time saved, decisions accelerated, revenue uplift, cost avoided, and scientific productivity gained
Develop domain pattern recognition in field force operations workflows to identify unarticulated AI opportunities
Own the Enterprise AI opportunity portfolio, including in-flight, queued, and de-prioritized opportunities and the rationale for decisions
Build frameworks, define success metrics, run analyses, and recommend engineering resource allocation
Evaluate and decline opportunities that will not produce scalable outcomes
Partner with forward deployed, full-stack, and data engineering leads to translate business problems into problem statements, prototypes, success metrics, and decision frameworks
Shape engagements end-to-end, defining scope, success criteria, exit conditions, and scaling pathways
Identify opportunities for reusable capabilities and platform leverage with engineering
Design the human-digital split, including digital worker ownership, human oversight, evaluation, and safety
Operate with senior business and scientific leaders to turn ambitions into fundable AI engagements
Build sponsor coalitions securing air cover, data access, and change-management commitment
Communicate AI impact to ELT and the board in terms of patient, science, and shareholder outcomes
Define Enterprise AI's value-realization framework
Run post-mortems and feed learnings into opportunity selection and engagement design
Continuously refine GSK's AI investment thesis

Requirements

What you’ll need

15 or more years of professional experience across pharma/life sciences, AI/ML product strategy, and product management or strategy roles in technology-led organizations
Experience taking at least one technology or AI initiative from problem framing through executive funding and into delivery
Prior responsibility with pharma field force operations, including rep coaching and enablement, omnichannel orchestration, or field analytics
Track record with modern AI/ML concepts, including LLMs, agentic systems, digital workers, the ML lifecycle, and data and evaluation patterns, demonstrated through hands-on prototyping
Experience operating as an individual contributor without direct reports, influencing engineering and business teams through frameworks and documented decision criteria
Experience in product management or product strategy, including opportunity sizing, roadmap development, prototyping, and stakeholder alignment
Regular use of field deployment processes, including customer/HCP segmentation, territory alignment, or call plan execution
Experience with field analytics and SFE KPI automation, including identifying execution gaps and producing actionable recommendations for the field
Proficiency using account planning or CRM systems such as Veeva or Salesforce
Experience partnering with sales leadership and brand teams to translate field performance data into targeting or resourcing decisions
Working knowledge of MLR and GxP compliance requirements applicable to field-facing recommendations and digital tools
Prior 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 with hands-on technology experience
Experience navigating GxP, regulatory, and data-governance requirements in pharma AI deployments
Experience with CRM, content, and data platforms used in field operations, such as Veeva CRM/Vault, Salesforce, IQVIA/Komodo data, or omnichannel engagement platforms

Benefits

Comp & perks

Annual bonus
Eligibility to participate in share-based long-term incentive program
Health care and other insurance benefits for employee and family
Retirement benefits
Paid holidays
Vacation
Paid caregiver/parental and medical leave
Accommodation or other assistance to apply, if required