Executive Director, Asset Strategy Leadership (AI/Drug Development)

Location: New York City, United States; office-based hybrid role with at least 50% of time in the office

Annual base salary: $297,000–$356,400, plus annual bonus, equity compensation, and benefits.

Company

hirify.global is a clinical-stage TechBio company using the AI-native hirify.global OS to integrate biology, chemistry, automation, data science, and clinical development for drug discovery.

What you will do

• Define asset strategy for small-molecule clinical programs in oncology and immunology/inflammation.
• Integrate competitive positioning, mechanistic differentiation, biomarker strategy, and patient segmentation into portfolio decisions.
• Translate hirify.global OS, ClinTech, proprietary data, and computational insights into strategic asset advantages.
• Develop and pressure-test competitive narratives for clinical assets to support leadership decisions, partnerships, and investor communications.
• Partner with clinical development, business development, finance, and platform leaders on resource allocation and portfolio trade-offs.

Requirements

• PhD in life sciences or a related scientific discipline.
• 10+ years of biotech or pharmaceutical experience with asset-level strategic leadership.
• Deep expertise in small-molecule therapeutics for oncology and immunology/inflammation.
• Experience using computational approaches and data-driven platforms for asset strategy and clinical decision-making.
• Ability to build strategic and competitive cases integrating mechanistic, regulatory, market, and competitive considerations.
• Strong financial acumen and executive presence, with the ability to present clear recommendations to senior leaders and external partners.

Nice to have

• Expertise in rare disease.

Culture & Benefits

• Annual bonus, equity compensation, and a comprehensive benefits package.
• Values include integrity, direct engagement, rapid learning, urgency for patients, ownership, accountability, and cross-functional collaboration.
• AI-powered platforms support data analysis, predictive modeling, real-world evidence integration, and patient stratification.