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Job Description

About the role

Takeda Research is constructing a Lab of Tomorrow built on AI, automation, new ways of working, and talent with the singular vision of delivering differentiated medicines to the clinic at speed and cost. To catalyze these efforts, Takeda is creating two complementary units: AI Research Accelerator (AIRx) and Discovery Automation & Robotics (DAR).

AIRx will have a group of a dedicated group of experienced biologic drug hunters with the autonomy of a biotech and the resources of a leading pharmaceutical company. It is designed to incubate the future AI-powered operating models for large molecule discovery and deliver candidates to the clinic at industry leading speed and success rates.

Purpose

As AIRx Biologics Discovery Lead, you will lead the end-to-end biologics discovery from lead generation, optimization to final candidate selection of 2–3 large molecule discovery programs within a unit deliberately designed to remove the structural overhead that slows programs down in large pharma. AI-enabled protein design, internal or externalized wet lab execution with state of Art platforms, and a direct line to governance: this is the environment elite biologic drug hunters have been waiting for.

You will work with highly experienced leaders with proven track record of delivering multiple large molecule INDs, top computational protein scientists, AI/ML specialists, CMC partners and translational biology experts in a model where the science, not the governance calendar, drives the pace and progress. This is a role for a leader who knows how to deliver speed and innovation integrating AI/ML based biologics  discovery, automated high throughput platforms with deep understanding of CMC as well as pharmacology of biologics drugs.

A proven track record of leading at least 2 biologic discovery programs to clinic is required.

Key Accountabilities

• Lead Biologics Discovery: Drive biologics discovery  for multiple programs from target and modality selection through candidate nomination, preclinical development transition, and IND filing
• Discovery strategy and implementation: Establish and execute discovery strategies across antibodies, bispecifics, fusion proteins, and emerging modalities with clear CMC and clinical line-of-sight
• Integrate AI and automation: Embed AI-driven protein design, computational modeling, and high-throughput experimental platforms to accelerate cycle times and improve design quality
• Enable decision-making: Evaluate and prioritize biologic candidates based on scientific, clinical, CMC, and commercial considerations; balance potency, selectivity, half-life, immunogenicity risk, and expression yield in go/no-go decisions
• Optimize molecules: Lead sequence optimization, affinity maturation, Fc engineering, and developability optimization through integrated computational and experimental approaches
• Manage external execution: Oversee CROs/CDMOs to ensure delivery of high-quality, decision-ready data on aggressive timelines
• External engagement: Represent AIRx externally; assess platform technologies, novel modalities, and serve as BD subject matter expert evaluating external assets
• Portfolio impact: Deliver biologics discovery with disciplined cost stewardship while contributing to a sustainable pipeline of biologics INDs

Qualifications & Competencies

• Expected Education and Industry Experience:
• Advanced degree in protein biochemistry, structural biology, molecular biology, immunology, or related life sciences (PhD, MD, or DVM); PhD strongly preferred; and
• 15+ years of industry experience with deep subject matter expertise in biologic drug discovery; at least 10 years in scientific leadership roles within large molecule programs
• Proven track record leading 5+ biologic programs across discovery from target inception to Candidate Nomination or beyond; minimum 2 biologic INDs required (antibody, bispecific, or fusion protein programs preferred)
• Deep knowledge of the biologic drug discovery and development process: target identification, discovery campaign strategies (yeast display, hybridoma, single B cell), lead optimization, developability assessment, and IND-enabling CMC and toxicology activ