Staff (Director), Commercial Enterprise Product Mgmt. - E2E Marketing Enablement

GSK • Durham, NC

2d • $171,600 - $286,000 • Hybrid

About The Position

GSK’s Enterprise AI team applies AI across the company by embedding AI product managers, forward deployed engineers, full-stack engineers, data engineers, and digital workers with scientific and business teams. This senior individual-contributor role owns a domain in the marketing enablement opportunity portfolio, including marketing automation, content supply chain and assembly, the marketing experience layer, campaign management, and performance measurement. The role sets the forward deployed strategy for its domain and partners closely with engineering and digital-worker teams to identify valuable opportunities, scope engagements, and measure business outcomes. It does not manage engineers.

The role is distinct from traditional enterprise product management: it focuses on creating AI products from ambiguous business problems, working with probabilistic systems and defining evaluation and human oversight, coordinating work across engineers and digital workers, and prototyping hands-on. Success is measured by outcomes rather than features shipped or system uptime.

The position reports to the VP, Commercial AI/ML Transformation. It is a hybrid role, with a primary location at London New Oxford Street and secondary locations in Philadelphia, Boston, and Durham. Business travel of 25% between the UK, USA, and India is expected. Relocation support is provided.

GSK’s Enterprise AI team builds and deploys AI products with scientific, clinical, and business teams, with a focus on production use and outcomes that matter to patients. GSK describes itself as a global biopharma company committed to diversity and inclusion.

Requirements

• 10 or more years of progressive experience spanning some combination of pharma or life sciences, AI/ML product strategy, and senior product management or strategy roles in technology-led organizations.
• Demonstrated experience identifying, scoping, prototyping, and shepherding high-value technology or AI initiatives from problem framing through funding and delivery.
• Strong working knowledge of pharma or other regulated-industry marketing enablement, particularly content supply chain, marketing automation, and the HCP-facing experience layer, including content assembly, campaign management, channel activation, and performance measurement.
• Experience building workflows for creative asset development and content submission, including MLR/MAC readiness, to support timely deployment across channels.
• Working knowledge of content lifecycle integrity and traceability, including maintaining links between derivative content and its approved source.
• Experience with omnichannel campaign execution and practices for measuring channel and content effectiveness.
• Technical fluency in modern AI/ML, including LLMs, agentic systems, digital workers, ML lifecycle, and data and evaluation patterns, sufficient to challenge engineers and scope realistically.
• Experience as a senior individual contributor who leads through influence, frameworks, and quality of thinking rather than headcount.
• Product management or product-strategy experience in discovery, opportunity sizing, roadmap shaping, prototyping, and stakeholder alignment; AI-centered products are preferred.
• Ability to operate within GxP, regulatory, and data-governance constraints.
• Comfort with CLI tools and codifying product management and user-research best practices into skills, plugins, and markdown files.
• Able to prototype rapidly, make evidence-based decisions, communicate clearly, and balance long-term patient impact with near-term delivery.

Responsibilities

• Identify, assess, and prioritize AI opportunities across marketing automation, content supply chain and assembly, the marketing experience layer, campaign management, and performance measurement.
• Build and maintain a structured domain opportunity pipeline ranked by impact, feasibility, and time-to-value.
• Quantify opportunity value and develop credible business cases for finance and senior business leaders.
• Shape the domain opportunity portfolio, document prioritization decisions, and contribute to the broader Enterprise AI portfolio.
• Recommend evidence-based trade-offs for allocating engineering resources and protect engineering focus from low-impact opportunities.
• Translate ambiguous business problems into clear problem statements, prototypes, success metrics, and decision frameworks for engineering teams.
• Define engagement scope, success criteria, exit conditions, and scaling pathways, and stay close to engagements during execution.
• Identify opportunities to turn one-off solutions into reusable capabilities.
• Design how engineers, digital workers, and business users divide tasks, hand off work, and apply evaluation and oversight.
• Engage VP-level business and scientific leaders to turn ambitions into concrete, fundable AI engagements.
• Build sponsor coalitions that secure data access, change-management commitment, and executive support.
• Communicate AI impact in terms of patient, scientific, and enterprise outcomes.
• Apply and improve the Enterprise AI value-realization framework, track outcomes, and conduct post-mortems to improve future opportunity selection.
• Shape at least two flagship engagements per year and set the forward deployed strategy for a bionic pod.

Benefits

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

What This Job Offers

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