Overview

This role will establish and lead a focused team to design and deploy next-generation agentic workflows that integrate directly into scientific research and the discovery of novel siRNA therapeutics.

The Director will play a central role in partnering with Research teams to embed AI into daily scientific workflows, enabling faster, more scalable, and more reproducible discovery processes. This is a hands-on leadership role combining computational biology, AI engineering, and platform design, with strong partnership across Research and IT to deliver durable, enterprise-aligned solutions.

You will join a growing Data & AI organization (20+ scientists and engineers) focused on transforming Alnylam into an AI-enabled research enterprise.

Responsibilities

Embed AI into Scientific Workflows (Primary Focus)

• Partner deeply with Research teams to embed AI-driven solutions into day-to-day scientific workflows
• Identify high-value opportunities to augment target and ligand discovery, and where appropriate, experimental design, data analysis, and decision-making
• Drive adoption and measurable impact through close collaboration with assay teams and scientific leadership

Develop and Deploy Agentic AI Workflows

• Architect and deploy multi-agent systems that automate and orchestrate core research activities, including:
  • • Target Discovery that encompasses human genetics datasets
    • Ligand Discovery for the delivery of siRNAs to novel tissues and cell types
    • Competitive intelligence (landscape monitoring, literature synthesis, target scouting)
    • Experimental design and hypothesis generation
    • Data analysis and interpretation
    • Knowledge synthesis from public and in-house data

• Integrate coding agents, research agents, and evaluation frameworks into scientific pipelines
• Ensure systems are scientifically grounded, validated, and continuously improved via lab feedback loops

Lead AI Strategy & Scientific Enablement

• Define and execute the AI roadmap for Research aligned to Alnylam's broader Data & AI strategy
• Drive adoption of AI to improve speed, quality, and scalability of research workflows
• Identify and prioritize AI use cases with clear scientific and operational impact

Build and Lead an AI Engineering & Science Team

• Recruit, lead, and develop a 3-5 person interdisciplinary team of data scientists and software engineers
• Establish a high-performance culture blending scientific rigor with agentic software engineering discipline
• Provide hands-on technical leadership in AI/ML, agent development, and production deployment

Integrate with Enterprise Data & IT Platforms

• Partner with IT to integrate AI workflows into the enterprise data platform and lakehouse environment
• Contribute to secure, scalable, and compliant AI systems across AWS and GCP environments
• Ensure alignment with data governance, security, and regulatory standards

Deliver Production-Grade Systems

• Oversee development of robust pipelines, model deployment frameworks, and evaluation systems
• Drive best practices in MLOps, reproducibility, and model validation
• Ensure AI solutions are reliable, scalable, and operationalized within Research

Support Computational Enablement of Design Efforts

• Provide computational and infrastructure support for ligand and antibody design efforts
• Work with the Alnylam Human Genetics (AHG) team to bring best-in-class AI workflows to human genetics analyses
• Partner with domain experts to ensure alignment with ongoing design strategies and scientific leadership

Qualifications

Education & Experience

• PhD (or MS with equivalent experience) in Computational Biology, Computer Science, AI/ML, or related field
• 10+ years of computational biology experience applying AI/ML in industry, preferably within drug discovery
• Proven experience leading technical teams and delivering AI-driven products or platforms in complex environments

Technical Expertise

• Demonstrated experience building agentic or multi-agent AI systems and workflow automation
• Programming experience (Python; full-stack development preferred)
• Experience developing production-grade ML/AI systems
• Experience with AWS (including Bedrock) and/or GCP environments
• Experience with modern LLM ecosystems and data integration at scale

Domain Knowledge

• Experience in biopharma research or drug discovery environments
• Understanding of experimental workflows and scientific data generation
• Familiarity with nucleic acid-based therapeutics is preferred

Preferred Qualifications

• Experience building AI systems integrated with lab-in-the-loop workflows
• Familiarity with enterprise data platforms and regulated environments
• Track record of deploying AI solutions in cross-functional organizations

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U.S. Pay Range

$193,200.00 - $289,800.00

The pay range reflects the full-time base salary range we expect to pay for this role at the time of posting. Base pay will be determined based on a number of factors including, but not limited to, relevant experience, skills, and education. This role is eligible for an annual short-term incentive award (e.g., bonus or sales incentive) and an annual long-term incentive award (e.g., equity).

Alnylam's robust Total Rewards package is designed to support your overall health and well-being. We offer comprehensive benefits including medical, dental, and vision coverage, life and disability insurance, a lifestyle reimbursement program, flexible spending and health savings accounts and a 401(k)with a generous company match. Eligible employees enjoy paid time off, wellness days, holidays, and two company-wide recharge breaks. We also offer generous family resources and leave. Our commitment to your well-being reflects our belief that caring for our people fuels the impact we create together.

Learn more about these and additional benefits offered by Alnylam by visiting the Benefits section of the Careers website: https://www.alnylam.com/careers