Position Summary
GSK's Enterprise AI team exists to translate the promise of AI into measurable impact across every major group at GSK — R&D, Medical, Commercial, Supply Chain, HR, Legal, Finance, and beyond. You will own a major slice of our Global Functions portfolio — across HR, Legal, Compliance, Procurement, Finance, and Corporate Communications — act as the strategic counterpart to the engineers and digital workers in your pod, and set the forward deployed strategy they execute against.
This is a senior individual contributor role for someone who can identify and shape high-value AI opportunities across Global Functions, build the case to fund and deploy against them, prototype hands on, and ensure engineers are working on what matters most. You will not manage engineers; you will shape what they build in your domain and how we measure whether it worked. Forward deployed teams are most powerful when paired with sharp opportunity selection: you will identify, size, and shape the highest-value AI opportunities in your domain, partner daily with engineering leads to scope and steer engagements end-to-end, and build the business and executive alignment the pod needs to land and scale.
Responsibilities
This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:
- Hunt for high-value AI opportunities across Global Functions — record-to-report, hire-to-retire, source-to-pay, contract-to-signature, and message development and approval — and develop a structured pipeline of AI products ranked by impact, feasibility, and time-to-value.
- Quantify value rigorously by building business cases that survive finance and senior business unit scrutiny — cycle time, cost-to-serve, risk reduction, hours returned, and spend under management.
- Develop domain pattern recognition in functional workflows — including how work flows between shared services, centers of expertise, and business partners — so you can spot AI-shaped problems the business itself hasn't yet articulated.
- Shape the opportunity portfolio in your domain, maintaining a living view of in-flight, queued, and de-prioritized opportunities, with the rationale for each decision, and feeding it into the broader Enterprise AI portfolio.
- Make trade-off recommendations — defining success metrics, running the analysis, and recommending where engineers go when business sponsors compete for the same resources.
- Push back, with evidence, on opportunities that won't move scalable outcomes, protecting engineering focus.
- Be the strategic counterpart to the forward deployed, full-stack, and data engineering leads in your domain, 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 — such as review, drafting, triage, reconciliation, monitoring, and query handling — where engineers and business users stay in the loop, and how evaluation and oversight make that safe.
- Design AI that is deployable in functional work, building SOX and financial controls, legal privilege and confidentiality, employee data privacy and works council requirements, anti-bribery and third-party due diligence, disclosure obligations, and EU AI Act high-risk requirements into every solution.
- Operate fluently with VP-level business and functional leaders, running conversations that turn fuzzy ambitions into concrete, fundable AI engagements, and moving between functions with very different cultures, risk appetites, and ways of working.
- Build sponsor coalitions, securing the data access, change-management commitment, and air cover your engagements require to succeed.
- Communicate impact clearly, in language that connects AI work back to patients, science, and enterprise outcomes.
- Apply the value-realization framework, using Enterprise AI's framework to measure every engagement in your domain and improving it with what you learn.
- Run honest post-mortems — capturing what worked, what didn't, and feeding those learnings back into how your domain selects opportunities and designs engagements.
Why You?
Basic Qualification
We are seeking professionals with the following required skills and qualifications to help us achieve our goals
- 10 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 funding and into delivery.
- Direct involvement in, or close partnership with, at least one Global Function — Legal & Compliance, HR, Finance, Corporate Communications, or Procurement — including its core end-to-end processes, such as record-to-report, hire-to-retire, source-to-pay, contract-to-signature, or message development and approval.
- Hands-on work with modern AI/ML concepts — including LLMs, agentic systems, and digital workers, the ML lifecycle, and data and evaluation patterns — demonstrated through prototyping.
- Prior responsibility for operating as an individual contributor without direct reports and influencing engineering and business teams through frameworks and documented decision criteria.
- Background in product management or product strategy, including opportunity sizing, roadmap development, prototyping, and stakeholder alignment.
- Working knowledge of the enterprise systems and data behind Global Functions, such as SAP, Workday, Ariba or Coupa, contract lifecycle management (CLM) tools, and case management or knowledge tools — including data ownership, quality, permissioning, and the unstructured documents and text where much of the value sits.
- Track record of identifying AI value in high-volume, knowledge-intensive work, such as review, drafting, triage, reconciliation, monitoring, or query handling.
- Working knowledge of the control and regulatory constraints on AI in functional work, including SOX and financial controls, legal privilege and confidentiality, employee data privacy and works councils, anti-bribery and third-party due diligence, disclosure obligations, and the EU AI Act's high-risk categories.
- Direct involvement in partnering with senior functional leaders, such as the CFO, CHRO, General Counsel, Chief Procurement Officer, or Chief Communications Officer, to turn transformation priorities into funded, measurable AI programs.
Preferred Qualification
If you have the following characteristics, it would be a plus
- Experience working across more than one Global Function.
- Experience navigating GxP, regulatory, and data-governance requirements in pharma AI deployments.
- Experience codifying product management and user research practices into AI-native tools — such as skills, plugins, and markdown files — and using the command line to automate daily work.
#GSK-LI #AGTech
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 (PLM), Product Roadmapping, Roadmap Development, Statistical Analysis, User Needs Analysis
• If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $171,600 to $286,000. • If you are based in another US location, the annual base salary range is $156,000 to $260,000. The US salary ranges take into account a number of factors including work location within the US market, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave. If salary ranges are not displayed in the job posting for a specific country, the relevant compensation will be discussed during the recruitment process.
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
