Principal (Senior Director), AI Product Management (Global Financial Services & Procurement)

GSK • Boston, MA

17h • $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 portfolio of AI products transforming Global Financial Services and Procurement worldwide, spanning sourcing and contracting, purchase-to-pay, invoice processing, supplier payments, travel and expenses, order-to-cash, and record-to-report. The role identifies and prioritizes high-value opportunities, evaluates proposed engagements for value, feasibility, and strategic fit, and develops the business cases, prototypes, and executive alignment needed to launch and scale them.

The position does not manage engineers. Instead, it shapes what engineering teams build, where they focus, and how outcomes are measured. It partners closely with forward-deployed, full-stack, and data engineering leads and senior finance and procurement stakeholders to turn business needs into clearly scoped, measurable AI engagements. Solutions should incorporate appropriate human oversight and strengthen financial controls, auditability, and compliance. The role also maintains the opportunity portfolio, determines resource priorities, identifies reusable capabilities, and establishes frameworks for measuring value and learning from deployments.

Requirements

• At least 15 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.
• Track record of taking at least one technology or AI initiative from problem framing through executive funding and into delivery.
• Direct involvement in source-to-pay or financial operations, including at least one of sourcing and contracting, purchase-to-pay, invoice processing, supplier payments, travel and expenses, order-to-cash, or record-to-report.
• Hands-on experience with modern AI/ML concepts, including LLMs, agentic systems, digital workers, the ML lifecycle, and data and evaluation patterns, demonstrated through prototyping.
• Experience operating as an individual contributor without direct reports and influencing engineering and business teams through frameworks and documented decision criteria.
• Product management or product strategy background, including opportunity sizing, roadmap development, prototyping, and stakeholder alignment.
• Working knowledge of systems and data supporting spend and transactions, such as SAP, Ariba or Coupa, invoice capture and accounts payable automation tools, and spend analytics.
• Knowledge of supplier master data quality, purchase order compliance, and duplicate or inconsistent records across systems.
• Track record of identifying AI value in high-volume transactional and commercial work, such as invoice matching and exceptions, supplier queries, spend classification, contract and clause review, or sourcing and negotiation support.
• Working knowledge of financial control and compliance requirements, including SOX, segregation of duties, audit evidence, anti-bribery and third-party due diligence, supplier risk and sanctions screening, and transaction tax requirements.
• Direct involvement in partnering with senior finance and procurement leaders to turn transformation priorities into funded, measurable AI or technology programs.

Nice To Haves

• Prior experience in forward-deployed engineering, applied AI, or an AI lab/center of excellence 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 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.

Responsibilities

• Identify and prioritize AI opportunities across Global Financial Services and Procurement, and develop a global portfolio ranked by impact, feasibility, and time-to-value.
• Build rigorous business cases using measures such as cost-to-serve, cycle time, touchless processing rates, working capital, spend under management, and realized savings.
• Develop expertise in source-to-pay and financial operations workflows, including breakdowns across Procurement, finance shared services, budget holders, and suppliers.
• Maintain a current portfolio of in-flight, queued, and de-prioritized opportunities, documenting the rationale for decisions.
• Develop prioritization frameworks, define success metrics, analyze competing demands, and recommend how engineering resources should be allocated.
• Decline opportunities that are unlikely to produce scalable outcomes, using evidence to protect engineering focus.
• Translate ambiguous business problems into problem statements, prototypes, success metrics, and decision frameworks for engineering teams.
• Shape engagements end to end by defining scope, success criteria, exit conditions, and scaling pathways before kickoff, and remain engaged during execution.
• Identify opportunities for reuse and platform leverage, and partner with engineering to develop reusable capabilities.
• Design the division of work between digital workers, engineers, and business users, including appropriate evaluation and oversight.
• Build SOX and financial controls, segregation of duties, audit evidence, third-party due diligence, and sanctions screening into AI solutions.
• Work with senior finance and procurement leaders to turn transformation priorities into concrete, fundable AI engagements.
• Build sponsor coalitions and secure executive support, data access, and change-management commitment for deployments.
• Communicate impact to executive leadership and the board, connecting AI outcomes to patients, science, and shareholder outcomes.
• Establish the value-realization framework used to measure impact across Enterprise AI deployments.
• Conduct post-mortems and incorporate lessons learned into 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