About the Role
Royalty Pharma is seeking an AI Engineer to join our small, high-impact AI team. We are a lean organization where every team member contributes across the full arc of the work — from research and method design through to deployed systems. This role leans toward the engineering end of that spectrum, focused on building reliable, production-grade AI systems that the investment team depends on every day. The ideal candidate is a strong builder who can move quickly from idea to working prototype, takes pride in implementation quality, and is equally comfortable engaging with the underlying science. This role will be based in our NYC office with in-person office attendance 3-4 days per week.
Responsibilities
• Design, build, and deploy AI-powered applications and workflows in support of the investment team
• Develop and maintain agentic systems capable of multi-step reasoning, tool use, and autonomous task execution
• Rapidly prototype and iterate on new ideas, moving from concept to working implementation with speed and rigor
• Partner with the AI Scientist and investment professionals to bring research ideas into production
• Apply large language models to quantitative research problems, including financial modeling, clinical and scientific literature, and structured life sciences datasets
• Profile and optimize AI systems for performance, reliability, and cost as they scale
• Own system observability and iterative improvement of deployed AI applications
Qualifications
• Bachelor's degree in Computer Science or related field required; Master's preferred
• 2-3 years of industry experience preferred; finance, quantitative research, or life sciences applications are ideal — candidates with experience applying ML or AI in financial contexts are particularly encouraged to apply
• Strong programming skills with a track record of delivering production software
• Deep hands-on experience with large language models and modern AI development practices
• Demonstrated ability to prototype quickly and iterate effectively in fast-moving, ambiguous environments
• Demonstrated understanding of agentic AI patterns and multi-agent system design
• Strong quantitative background; experience applying AI to quantitative or financial research is a plus
• Familiarity with life sciences data — including clinical trial data, drug development pipelines, and regulatory submissions — is a meaningful differentiator
• Experience in biopharma, financial services, or at the intersection of both is an advantage
