Project Team Lead

Responsibilities

• Lead complex cross-functional project teams advancing programs from concept through preclinical proof-of-concept
• Be accountable for overall scientific direction, team effectiveness, and readiness for stage-gate decisions
• Develop integrated program strategies aligning scientific objectives, timing, resourcing, and budgets
• Facilitate team discussions and drive timely go/no-go recommendations
• Partner with Portfolio Leads to shape portfolio strategy and refine program direction
• Represent programs in governance forums and influence senior leadership decisions
• Drive execution across wet lab, computational, platform, and translational workstreams
• Identify and advance therapeutic opportunities using biological and platform insights
• Manage program resource plans and budget assumptions
• Mentor scientists and research leads to strengthen technical depth and leadership

Requirements

• PhD, MD, or MD/PhD in life sciences or a relevant discipline
• 10+ years of experience leading cross-functional research or program teams in biotech or pharma
• Proven success leading complex programs through discovery and translational stages
• Strong scientific grounding in biology, experimental design, and data interpretation
• Experience driving decisions in matrixed environments without direct line authority
• Strong operational leadership in planning, prioritization, and resource management
• Excellent written and verbal communication skills

Preferred Qualifications

• Experience with protein therapeutics, peptides, or conjugate-based approaches
• Familiarity with computational protein design or machine learning-enabled discovery
• Experience with target selection, validation, and translational strategy (PK/PD)
• Familiarity with IND-enabling studies and early clinical development
• Comfort using LLM-enabled tools and agentic workflows for scientific planning

About the Company

Generate:Biomedicines is a clinical-stage generative biology company pioneering the AI revolution in drug design and development. By integrating machine learning with large-scale experimentation, the company aims to design proteins with defined biological intent to reduce the uncertainty, time, and cost of developing protein-based medicines.