Teams at RA Capital Management

Build and operate production-grade healthcare data pipelines, models, and AI-enabled workflows. Develop Python and SQL solutions for data validation, reconciliation, and standardization; connect large language models with enterprise data, APIs, and internal tools; create governed LLM-to-SQL and LLM-to-GraphQL access frameworks; and implement agentic workflows, monitoring, observability, validation, and governance. Collaborate with engineering teams, vendors, and stakeholders to deliver reliable, compliant data and AI platforms.

Supports investor onboarding, documentation, reporting, subscriptions, redemptions, AML/KYC processes, transfer requests, tax reporting, cash clearance, and capital activity reconciliation. Coordinates with fund administrators, legal, accounting, finance, and investor relations teams; manages investor inquiries and due diligence requests; verifies quantitative reports; maintains process documentation and client service workflows; and supports marketing and due diligence materials.

Design and deploy AI systems that convert unstructured healthcare, scientific, and financial information into decision-relevant insights. Own applied AI projects from problem definition through deployment, evaluation, and improvement, using NLP, RAG, knowledge graphs, embeddings, entity extraction, and agentic systems. Develop evaluation frameworks, ensure data quality and reproducibility, and collaborate with investment professionals and senior stakeholders to support investment research and decision-making.