Principal (Senior Director), Commercial Enterprise AI Product Mgmt., Field Force Effectiveness

GSK • Philadelphia, PA

2d • $177,750 - $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 strategic direction for a global portfolio of AI solutions supporting field force effectiveness. The role identifies and prioritizes opportunities, develops prototypes and business cases, and guides forward-deployed teams toward high-impact work. It does not manage engineers; instead, it shapes what teams build, where they focus, and how outcomes are measured.

The position focuses on field force workflows such as rep coaching and enablement, omnichannel orchestration, and field analytics. It partners with engineering and business leaders to frame problems, define engagements and success criteria, secure executive sponsorship, guide safe human-digital workflows, and identify opportunities to scale reusable capabilities. It also establishes value-realization practices and communicates impact to senior leaders, connecting AI initiatives to patient, scientific, and business outcomes.

Requirements

• 15 or more years of professional experience across some combination of pharma or 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 for 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 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 field recommendations.
• Proficiency with account planning or CRM systems, such as Veeva or Salesforce, to execute and track field plans.
• 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.

Nice To Haves

• 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 combined 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.

Responsibilities

• Identify, size, and prioritize AI opportunities across field force effectiveness, including rep coaching and enablement, omnichannel orchestration, and field analytics.
• Develop and maintain a global AI product portfolio ranked by impact, feasibility, and time-to-value, including clear rationales for in-flight, queued, and de-prioritized opportunities.
• Build rigorous business cases and quantify value, such as cycle time saved, faster decisions, revenue uplift, cost avoided, and scientific productivity gained.
• Develop expertise in field force operations workflows to identify opportunities the business has not yet articulated.
• Establish prioritization 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 ambiguous business problems into problem statements, prototypes, success metrics, and decision frameworks.
• Shape engagements end-to-end by defining scope, success criteria, exit conditions, and scaling pathways before kickoff, and remain engaged during execution.
• Identify when one-off solutions could become reusable capabilities and work with engineering to assess platform leverage.
• Design the division of work between digital workers, engineers, and business users, including evaluation and oversight approaches.
• Lead executive conversations that turn ambitions into concrete, fundable AI engagements.
• Build sponsor coalitions and secure executive support, data access, and change-management commitment for deployments.
• Communicate the impact of AI work to executive leadership and the board, connecting it to patients, science, and shareholder outcomes.
• Establish a value-realization framework for measuring impact across Enterprise AI deployments.
• Conduct post-mortems, capture lessons learned, and apply them to 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