Parexel

Vice President, AI Enablement

Parexel

full-time

Posted on:

Location Type: Remote

Location: United Kingdom

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Job Level

Lead

Tech Stack

AzureCloud

About the role

  • Define and evolve Parexel’s enterprise AI strategy, roadmap, and investment portfolio.
  • Identify priority use cases aligned to business value, feasibility, and regulatory constraints.
  • Conduct AI maturity assessments and establish long‑term capability-building plans.
  • Define standards for model lifecycle management, validation, auditability, and transparency.
  • Ensure compliance with GxP, global regulatory guidance, and responsible AI principles.
  • Drive scalable architecture for GenAI, ML operations, retrieval‑augmented generation, and secure model hosting.
  • Lead AI product teams delivering enterprise and function‑specific solutions.
  • Align AI programs with broader Data & Technology strategy and transformation goals.
  • Build and lead a global organization of AI product managers, engineers, data scientists, and AI governance specialists.

Requirements

  • 15+ years in data science, AI/ML, or technology leadership roles; at least 7 years in executive or senior leadership.
  • Deep knowledge of clinical research processes, clinical data lifecycle, and pharmaceutical/life sciences regulatory expectations.
  • Experience implementing enterprise AI platforms (GenAI, MLOps, data pipelines, automation).
  • Proven success operationalizing large-scale AI programs in GxP or other highly regulated industries.
  • Familiarity with emerging AI regulations (EU AI Act, FDA, EMA expectations).
  • Experience with cloud-based AI ecosystems (Azure preferred).
Benefits
  • Opportunity to work on innovative projects at the forefront of the industry.
  • Collaborative and inclusive work environment that values your expertise.
  • Professional advancement and development opportunities.
  • Work life balance and flexible working hours.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI strategymachine learningmodel lifecycle managementdata pipelinesautomationGenAIMLOpsAI maturity assessmentsscalable architecturevalidation
Soft Skills
leadershiporganizational skillscommunicationstrategic alignmentteam building