The GCF6 Agentic AI Lead – Protein Design & Molecular Engineering is a senior scientific and technical leader responsible for defining and driving AI-enabled workflows that accelerate protein engineering, structure prediction, molecular design, and related discovery activities.
This role combines deep domain expertise in computational biology and molecular engineering with a strong understanding of emerging AI technologies, including foundation models, scientific AI, and agentic systems.
The leader identifies high-value scientific opportunities, designs AI-assisted workflows, and partners with ML engineers to build reusable agentic capabilities that enhance scientific productivity and decision-making.
This role serves as the primary scientific lead for AI applications in protein engineering and molecular design.
Core Responsibilities
Scientific AI Strategy
Develop and maintain a roadmap for AI-enabled capabilities supporting:
Protein engineering
Structure prediction
Protein design
Motif discovery
Protein-ligand interactions
Sequence-function analysis
Molecular optimization
Identify opportunities where AI agents, scientific models, and automation can significantly improve scientific workflows and outcomes.
Agentic Workflow Design
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