AI-Driven Nonclinical Writing Lead (Hybrid)

Alnylam Pharmaceuticals; Cambridge (MA); Hybrid; USD 157,000 - 212,000; Full time

Job summary

Alnylam Pharmaceuticals in Cambridge, MA, seeks an Associate Director for Nonclinical Writing AI Innovation to define and drive an AI-enabled strategy across nonclinical workflows. This hybrid role focuses on scalable digital solutions, data integrity, and regulatory documentation through AI tools, in collaboration with scientific, IT, quality, and regulatory teams.

The ideal candidate has 5–10 years in AI-enabled transformation within life sciences, plus hands-on experience with LLM platforms,

Qualifications

• Bachelor's degree in a relevant scientific field required; Master's or PhD preferred.
• Approximately 5-10 years of progressive experience in AI, digital transformation, technology enablement, computational life sciences, nonclinical regulatory writing, CRO, or related R&D environments.
• Demonstrated expertise in authoring a wide range of regulatory documents (eg, nonclinical study protocols and reports, IBs, regulatory submissions).
• Demonstrated experience translating scientific or business needs into scalable AI-enabled solutions, including use case prioritization, implementation, adoption, and value measurement.
• Hands-on fluency with leading AI and LLM platforms, automation capabilities, agentic AI concepts, low-code prototyping, and responsible human-in-the-loop deployment models.
• Strong understanding of life sciences, R&D, nonclinical electronic data systems, program management solutions, regulatory documentation workflows, and regulated or IP-sensitive operating environments.
• Proven ability to lead complex cross-functional initiatives without direct authority and communicate effectively with technical, scientific, operational, and senior leadership audiences.
• Preferred experience with enterprise AI tools, data architecture or cloud platforms, AI governance frameworks, vendor management, consulting, or change management programs.
• Knowledge and understanding of global health authority requirements preferred, including CDER/CBER, OECD, ICH guidelines, and eCTD submission requirements, SEND.

Responsibilities

• Lead intake, prioritization, and ROI tracking for AI use cases that improve productivity and operational efficiencies.
• Partner with scientific, regulatory, quality, IT, InfoSec, legal, procurement, and business teams to pilot, deploy, and scale AI-enabled solutions.
• Accountable for nonclinical writing deliverables across many programs to improve data verification, quality, and authoring regulatory documents using AI tools.
• Define and execute an AI strategy and roadmap aligned with Early Development, Nonclinical Writing, and organizational innovation priorities.
• Champion adoption of AI, automation, and digital enablement approaches across workflows, including governance, quality control, reporting, regulatory dossiers, training, and knowledge management.
• Evaluate emerging technologies, enterprise AI platforms, and vendor solutions to support responsible, secure, and fit-for-purpose implementation.
• Establish best practices to increase productivity, data quality, reproducibility, responsible AI use, and compliance with applicable regulatory and GXP expectations.
• Build AI capability through training, coaching, change-champion networks, and executive-ready communications that support sustainable adoption.

Skills

AI platform fluency

Low-code prototyping

Cross-functional leadership

Automation capabilities

Regulatory writing

Education

Bachelor's degree in a relevant scientific field

Master's or PhD preferred

Tools

Enterprise AI tools

Cloud platforms

Job description

Alnylam Pharmaceuticals in Cambridge, MA, seeks an Associate Director for Nonclinical Writing AI Innovation to define and drive an AI-enabled strategy across nonclinical workflows. This hybrid role focuses on scalable digital solutions, data integrity, and regulatory documentation through AI tools, in collaboration with scientific, IT, quality, and regulatory teams.

The ideal candidate has 5–10 years in AI-enabled transformation within life sciences, plus hands-on experience with LLM platforms,