Project Team Lead (Cardio-Renal-Metabolic)

TL;DR

Project Team Lead (Biotech/AI): Leading cross-functional scientific teams to advance programs from concept through preclinical proof-of-concept with an accent on cardio-renal-metabolic therapeutic areas. Focus on shaping integrated research plans, driving execution across wet lab and computational workstreams, and guiding programs through key decision gates.

Location: Must be based in Somerville, MA

Salary: $177,000 – $260,000 USD

Company

hirify.global is a clinical-stage generative biology company pioneering the AI revolution in drug design and development.

What you will do

• Lead complex cross-functional teams advancing programs from concept and early discovery through preclinical proof-of-concept.
• Develop integrated program strategies aligning scientific objectives, timing, resourcing, budgets, and decision points.
• Drive execution across wet lab, computational, platform, and translational workstreams to ensure scientific rigor.
• Represent programs in governance forums and influence senior leadership through evidence-based recommendations.
• Identify and advance therapeutic opportunities by integrating biology, translational relevance, and platform capabilities.
• Mentor scientists and research leads to strengthen technical depth and collaborative leadership.

Requirements

• PhD, MD, or MD/PhD in life sciences or a relevant discipline for therapeutic discovery.
• 10+ years of experience leading cross-functional research or program teams in biotech, pharma, or academia.
• Demonstrated success leading complex programs through discovery and translational stages.
• Strong grounding in biology, experimental design, and data synthesis across technical domains.
• Experience shaping program strategy and driving decisions in matrixed environments at a Director-level scope.
• Excellent communication skills with the ability to translate complex scientific issues for leadership audiences.

Nice to have

• Experience with protein therapeutics, peptides, and conjugate-based approaches.
• Familiarity with computational protein design and machine learning-enabled discovery.
• Knowledge of target selection, target validation, and IND-enabling studies.
• Understanding of translational strategy, including PK/PD considerations.
• Comfort using LLM-enabled tools and agentic workflows to support scientific planning.

Culture & Benefits

• Opportunity to work in a fast-moving, entrepreneurial environment at the forefront of AI-driven drug design.
• Collaborative team culture grounded in accountability, transparency, and urgency.
• Eligible for an annual bonus and equity compensation.
• Competitive benefits package.
• A role with significant influence across research, platform, and portfolio decisions.