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Head of Biologics Engineering Generation Platform Innovation

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: Takeda Pharmaceutical Co.
Full Time position
Listed on 2026-10-04
Job specializations:
  • Research/Development
    Biotech Research, Research Scientist, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 212000 - 333190 USD Yearly USD 212000.00 333190.00 YEAR
Job Description & How to Apply Below
Job Description

We are seeking an exceptional scientific leader to join the Global Biologics Leadership Team as Head of Biologics Engineering & Next-Generation Platform Innovation.

This leader will define and execute the strategy for next-generation biologics beyond conventional monoclonal antibodies, while driving programs from early discovery through candidate selection and IND-enabling development. They will combine deep expertise in biologics discovery, engineering, and translational science with emerging capabilities in AI-driven design, computational biology, and automated experimentation to build a differentiated and sustainable innovation engine.

The successful candidate will bring a strong Drug Hunter mindset, a track record of delivering impactful pipeline assets, and the vision to create platform capabilities that accelerate the discovery of transformative medicines. They will be responsible for advancing both near-term program value and long-term technology leadership while developing the next generation of biologics scientists and leaders.

Key Responsibilities

1. Define and Lead the Next Generation of Biologics Innovation

  • Establish the scientific vision, strategy, and portfolio framework for biologics beyond traditional monoclonal antibodies, including multispecific, conditionally active, multi functional and highly developable emerging biologic modalities.
  • Build a differentiated platform strategy spanning molecule design, engineering, develop ability, manufacturability, translational science, and clinical application.
  • Identify and evaluate transformative technologies, external partnerships, licensing opportunities, and strategic collaborations.
  • Serve as a senior scientific leader and trusted advisor to executive leadership, governance committees, and the external scientific community.

2. Deliver High-Impact Programs from Discovery to IND

  • Lead biologics programs from target validation through lead optimization, candidate nomination, and IND-enabling development.
  • Drive rigorous, data-driven decision making across targets, modalities, molecules, and portfolios.
  • Integrate expertise across discovery biology, protein engineering, translational medicine, DMPK, safety, CMC, regulatory, and clinical development.
  • Ensure programs are grounded in strong human biology, clear differentiation, robust develop ability, and a compelling probability of technical and clinical success.
  • Balance scientific ambition, portfolio prioritization, risk management, resource investment, and executional excellence.

3. Build a World-Class Multispecific Biologics Platform

  • Create a scalable discovery and engineering platform capable of generating differentiated multispecific biologics with superior pharmacological and translational properties.
  • Advance next-generation design approaches through the integration of protein engineering, structural biology, computational design, AI-enabled molecule generation, and advanced screening technologies.
  • Establish design principles that optimize potency, specificity, conditional activity, tissue selectivity, manufacturability, and therapeutic index.
  • Translate platform innovation into measurable gains in speed, quality, differentiation, and pipeline productivity.

4. Establish an AI- and Automation-Enabled Biologics Engineering Engine

  • Partnering with external and Takeda AI leaders, build a computational prediction driven, display technology enabled lead optimization and engineering workflow to convert early biologics lead molecules to transformative lead candidates.
  • Drive adoption of automation, robotics, high-throughput experimentation, modern laboratory informatics, and closed-loop discovery systems.
  • Develop an enterprise knowledge framework that enables biological, experimental, clinical,…
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