Data Engineering Intern

Imagine if you had the skills, knowledge, and teammates to both understand the root of the world’s most pressing problems and build the technologies and companies best positioned to solve them. RA Capital has done exactly that for more than two decades, backing bold ideas in medicines to further human health and now expanding into Planetary Health to improve how efficiently we utilize the world’s precious resources.

RA Capital is among the leading providers of capital and services to the most promising innovators in the world.  We invest flexibly—seed to IPO and beyond, anywhere in the world—with $10 B+ under management and a culture that prizes curiosity, rigor, and collaborative debate. We are investors who not only fund companies but get elbow deep in building them. From helping them recruit talent to helping them recruit patients for their studies to helping match them to strategic partners and even going to Washington to win reforms, RA Capital’s large team has people with nearly every relevant expertise one might need to turn an idea into a cure that actually helps people. 

If you live for first-principles problem-solving with great colleagues, thrive on complexity, and want to do meaningful work that ripples across industries and ecosystems, you’ll feel at home at RA Capital. Here, questions are welcomed, ideas are tested, and victories are shared. Even our lawyers are creative and engaging. And don’t get us started on our compliance team’s wicked sense of humor; nothing about what we do is boring. 

Are you ready to bring your creativity, discipline and collaborative spirit to help us invent the future? Join us and you’ll collaborate daily with investors, founders, physicians, biologists, engineers, economists, and reform advocates who think in systems and act with urgency.  

Join us to invent a happier, healthier, more productive future - and have fun doing it.

 

About the Team

RA Capital’s Data Engineering team builds the enterprise data platform that powers research, investment, and operational workflows across the firm.

In addition to traditional data infrastructure, we are actively exploring AI-native ways of interacting with healthcare data, enabling users to query complex datasets using natural language through LLM-powered, governed, and auditable systems.

Our work sits at the intersection of healthcare, data, and applied AI, with a strong focus on generating insights that directly inform investment decisions.

About the Role

We are seeking a research-oriented Software Engineer Intern to explore how AI can transform access to and understanding of healthcare data.

This role is ideal for candidates interested in applied AI, experimentation, and data-driven problem solving. You will work on prototyping and evaluating LLM-driven approaches to querying and reasoning over structured healthcare datasets, and help translate real-world research questions into data and AI solutions.

While you will write code and work with data systems, the primary focus is on exploration, experimentation, and insight generation, rather than production system ownership.

Key Responsibilities

• Prototype and evaluate LLM-based approaches for querying and analyzing healthcare data
• Conduct experiments to assess accuracy, robustness, and limitations of AI-driven data access
• Work with structured datasets (e.g., claims, provider data) to understand data characteristics and challenges
• Translate research and investment questions into data and AI experiments
• Collaborate with engineers and researchers to iterate on AI-driven data access patterns
• Analyze experimental results and communicate findings, trade-offs, and recommendations
• Stay current with advancements in LLMs, AI agents, and data access frameworks

Key Skills & Experience

• Strong interest in applied AI, LLMs, and data-driven research
• Experience with Python for experimentation, data analysis, or prototyping
• Familiarity with SQL and structured data concepts
• Exposure to machine learning, NLP, or LLM-related projects is a plus
• Ability to think critically about model behavior, evaluation, and limitations
• Strong communication skills and ability to present findings clearly
• Strong problem-solving abilities and investigative mindset
• Ability to work in a collaborative, mentorship-driven environment

Key Qualifications

• Currently pursuing a Master’s or PhD in Computer Science, Data Science, AI, or a related field
• Research experience (academic or industry) in AI, ML, or data-related areas is a strong plus
• Excellent English com