Senior Enterprise AI Product Lead, Field Force

GlaxoSmithKline; Boston (MA); On-site; USD 196,000 - 326,000; Full time

Benefits offered by this job

Annual bonus

Long-term incentive program

Health insurance

Retirement benefits

Paid holidays

Vacation

Job summary

GSK is seeking a senior Enterprise AI individual contributor to identify high-value AI opportunities across the field force, shape an AI portfolio, and drive measurable impact. You will work with forward deployed teams and engineers to frame problems, prototype solutions, and secure executive sponsorship.

In this role you will translate business problems into clear statement-of-work, success metrics, and scalable engagements, partnering with sales and brand teams to realize field analytics and

Qualifications

• 15+ 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, and digital workers, 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, 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.

Responsibilities

• 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 rigorously by building business cases that hold up with finance and executive sponsors - cycle time saved, decisions accelerated, revenue uplift, cost avoided, scientific productivity gained.
• Develop domain pattern recognition in field force operations workflows so you can spot AI-shaped problems the business itself hasn't yet articulated.
• Own the Enterprise AI opportunity portfolio, maintaining a living view of in-flight, queued, and de-prioritized opportunities, with the rationale for each decision.
• Make hard trade-off calls - building the framework, defining success metrics, running the analysis, and recommending where engineers go when business units compete for the same resources.
• Say no, with evidence, to opportunities that look attractive but won't move scalable outcomes, protecting engineering focus.
• Be the strategic counterpart to the forward deployed, full-stack, and data engineering leads, translating ambiguous business problems into crisp problem statements, prototypes, success metrics, and decision frameworks engineers can build against.
• Shape engagements end-to-end - defining scope, success criteria, exit conditions, and scaling pathways before kick-off, then staying close as engineers execute.
• Surface re-use and platform leverage, spotting when a one-off solution should become a reusable capability and working with engineering to make that case.
• Design the human-digital split, deciding which tasks the pod's digital workers own, where engineers and business users stay in the loop, and how evaluation and oversight make that safe.
• Operate fluently with senior business and scientific leaders, running executive conversations that turn fuzzy ambitions into concrete, fundable AI engagements.
• Build sponsor coalitions, securing the air cover, data access, and change-management commitment that engineering deployments require to succeed.
• Communicate impact clearly, telling the value story to ELT and the board, in language that connects AI work back to patients, science, and shareholder outcomes.
• Define how we keep score, establishing the value-realization framework Enterprise AI uses to measure impact across deployments.
• Run honest post-mortems - capturing what worked, what didn't, and feeding those learnings back into opportunity selection and engagement design.
• Continuously sharpen the investment thesis on where AI most belongs at GSK, and where it doesn't.

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

Product Roadmapping

Roadmap Development

Statistical Analysis

User Needs Analysis

Tools

Veeva CRM

Salesforce

IQVIA/Komodo

Job description

GSK is seeking a senior Enterprise AI individual contributor to identify high-value AI opportunities across the field force, shape an AI portfolio, and drive measurable impact. You will work with forward deployed teams and engineers to frame problems, prototype solutions, and secure executive sponsorship.

In this role you will translate business problems into clear statement-of-work, success metrics, and scalable engagements, partnering with sales and brand teams to realize field analytics and