Director, Research AI

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.

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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
• 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
• Familiarity with nucleic acid-based therapeutics is preferred

• Experience building AI systems integrated with…