Executive Director, AIRx Program Lead: Biologics

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 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.

As AIRx Biologics Program Lead, you will own the end-to-end scientific and strategic direction 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, and a direct line to governance: this is the environment elite biologic drug hunters have been waiting for.

• Lead and manage multiple biologic drug discovery projects in an AI-forward manner with urgency; oversee the entire discovery process from modality selection through preclinical development and IND filing
• Define, articulate, and evolve the program strategy for antibody, bispecific, fusion protein, or other large molecule modalities; build the medicine vision and early asset strategy including develop ability and manufacturability considerations
• Evaluate and prioritize biologic candidates based on scientific, clinical, CMC, and commercial considerations; balance potency, selectivity, half-life, immunogenicity risk, protein stability and expression yield in go/no‑go decisions
• Lead and enable rapid, AI-enabled Design and Test cycles for protein engineering; ensure generative protein design and structure‑prediction outputs are translated into clear experimental recommendations and fast, decisive go/no‑go outcomes
• Drive sequence optimization, affinity maturation, Fc engineering, and formulation‑ready candidate selection using integrated computational and experimental platforms
• Partner with Clinical and Translational teams to refine asset strategy; ensure clinical line of sight from early discovery including patient selection, biomarker strategy, and dose projection from PK/PD modeling
• Manage external CROs and CDMOs providing protein expression, purification, in‑vitro pharmacology, and GLP toxicology services; ensure timelines are met and data is decision‑ready
• Represent Takeda externally for AIRx Biologics; evaluate external opportunities including platform technologies, novel modalities, and in‑licensing candidates; serve as BD ambassador
• Ensure programs are delivered at pace with disciplined cost stewardship, contributing to a sustainable, high‑quality pipeline of biologic INDs and informing broader portfolio strategy

• Advanced degree in protein biochemistry, structural biology, molecular biology, immunology, or related life sciences (PhD, MD, or DVM);
  PhD strongly preferred
• 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 3 biologic INDs required (antibody, bispecific, or fusion protein programs preferred)
• Deep knowledge of the biologic drug discovery and development process: target identification, hit generation (phage/yeast display, hybridoma, single B cell), lead optimization, develop ability assessment, and IND‑enabling CMC and toxicology activities
• Expertise in protein engineering principles: affinity maturation, CDR optimization, Fc engineering, bispecific/multispecific antibody formats, linker design, and fusion protein architecture
• Strong AI/ML exposure and digital‑forward scientific mindset; experience leveraging AI in protein design
• Solid understanding of large molecule DMPK:
  FcRn‑mediated recycling,…