Principal (Senior Director), AI Product Management (Legal & Compliance)

GSK • Boston, MA

17h • $177,750 - $325,875

About The Position

GSK’s Enterprise AI team translates AI into measurable impact across groups including R&D, Medical, Commercial, Supply Chain, HR, Legal, and Finance. This senior individual contributor will set the strategic direction and forward-deployed strategy for a portfolio of AI solutions transforming Legal and Compliance globally, spanning areas such as contracting, litigation, investigations, privacy, and compliance monitoring. The role identifies and prioritizes high-value opportunities, prototypes hands-on, and ensures engineering teams focus on the highest-impact work. It does not manage engineers; instead, it shapes what they build, where they focus, and how results are measured.

The role combines rigorous opportunity assessment and business-case development with close partnership with forward-deployed, full-stack, and data engineering leads and senior legal and compliance leaders. It frames ambiguous business needs as fundable, measurable engagements, guides deployments from scope through execution and scaling, and builds appropriate human oversight, evaluation, privilege preservation, explainability, and other safeguards into legal AI. It also establishes Enterprise AI’s value-realization approach and uses deployment learnings to improve future opportunity selection and engagement design.

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 or close partnership with legal and compliance work in at least one area: contracting, litigation and investigations, compliance monitoring, privacy, or General Counsel advisory work.
• Hands-on work 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.
• Background in product management or product strategy, including opportunity sizing, roadmap development, prototyping, and stakeholder alignment.
• Working knowledge of legal technology and related data, including contract lifecycle management, matter management, eDiscovery and investigation platforms, and legal AI tools such as Harvey or Legora; familiarity with unstructured, confidential, and privileged data distributed across systems with uneven metadata.
• Track record of identifying AI value in high-judgment, document-heavy work such as contract review and drafting, clause extraction, first-pass document review, investigation triage, policy queries, regulatory horizon scanning, or compliance monitoring.
• Working knowledge of professional, regulatory, and ethical constraints on legal AI, including legal privilege, litigation hold, eDiscovery defensibility, anti-bribery and corruption obligations, data privacy and residency, and professional responsibility standards governing lawyers’ use of AI.
• Direct involvement in partnering with senior legal and compliance leadership 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 high-value AI opportunities across Legal and Compliance and develop a global portfolio ranked by impact, feasibility, and time-to-value.
• Build rigorous business cases for AI initiatives, quantifying outcomes such as review hours returned, contract cycle time, outside counsel spend avoided, monitoring coverage, and risks surfaced earlier.
• Develop understanding of legal and compliance workflows to identify suitable AI opportunities.
• 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 opportunities, 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 staying engaged during execution.
• Identify opportunities for reuse and platform leverage, and work with engineering to assess when one-off solutions should become reusable capabilities.
• Design the division of work between AI digital workers, engineers, and business users, including evaluation and oversight for tasks such as contract review and drafting, clause extraction, document review, investigation triage, policy queries, and regulatory horizon scanning.
• Build legal AI solutions with appropriate accuracy, explainability, privilege preservation, litigation hold, defensible eDiscovery, anti-bribery and corruption obligations, data privacy and residency, and professional responsibility safeguards.
• Work with senior legal and compliance leaders, including the General Counsel, Chief Compliance Officer, practice leads, and legal operations, to turn transformation priorities into concrete, fundable AI engagements.
• Build sponsor coalitions that secure executive support, data access, and change-management commitment for engineering 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 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