Director, Research AI

Alnylam Pharmaceuticals•Cambridge, MA

11d•$193,200 - $289,800

About The Position

Alnylam Pharmaceuticals is seeking a highly technical and strategic Director of Artificial Intelligence to lead the expansion of AI capabilities across the Research organization. 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.

Requirements

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
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
Experience in biopharma research or drug discovery environments
Understanding of experimental workflows and scientific data generation

Nice To Haves

Familiarity with nucleic acid-based therapeutics is preferred
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

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.