Lead-AI Strategy, Product & Program Management

Role Summary

The Product Manager will lead the planning, prioritization, and execution of AI/ML initiatives across pharmaceutical R&D and manufacturing to support R&D and manufacturing programs in infectious disease and prophylactic antibodies, mRNA therapeutics, gene editing, and CAR-T/cell therapy. The role will define the AI roadmap, product strategy, governance, and cross-functional delivery of AI solutions supporting drug discovery, clinical development, manufacturing, and business operations.

This position serves as the bridge between scientific, technical, and business teams, ensuring AI programs deliver measurable impact and align with enterprise priorities.

Key Responsibilities

• Define and execute the AI/ML strategy and roadmap aligned with R&D and business priorities.
• Lead AI product and project management, including prioritization, timelines, resource planning, and execution.
• Translate scientific and business needs into AI use cases, product requirements, and delivery plans.
• Manage cross-functional teams across AI/ML, bioinformatics, clinical, manufacturing, IT, and business stakeholders.
• Establish information governance, KPIs, model performance tracking, and adoption frameworks.
• Drive deployment of AI solutions in:
• Drug discovery and computational design
• Clinical trials and competitive intelligence
• Manufacturing and process optimization
• Knowledge management and enterprise AI
• Evaluate emerging AI technologies, vendors, and partnerships to strengthen capabilities.
• Ensure compliance with data governance, security, GxP, and regulatory requirements where applicable.

Qualifications

• MS/PhD in Life Sciences, AI/ML, Bioinformatics, Engineering, Computer Science, Business, or related field.
• 8-12+ years of experience in pharmaceutical, biotech, healthcare, or technology sectors.
• 3-5+ years of experience in AI product management, program management, or digital transformation.

Technical & Business Skills

• Strong understanding of AI/ML, data science, and pharmaceutical R&D workflows.
• Working technical fluency to evaluate AI/ML architectures, model performance claims, and vendor platforms (build vs. buy assessments) without relying solely on vendor representations.
• Experience managing AI products, digital platforms, or enterprise transformation programs.
• Knowledge of Agile, product lifecycle management, and project execution methodologies.
• Familiarity with LLMs, generative AI, cloud platforms, and data infrastructure, and AI/model governance practices (e.g., model risk management explainability, responsible AI frameworks) required given GxP and regulatory context.
• Strong stakeholder management, communication, and leadership skills.