AI-Driven Healthcare Data Engineer

RA Capital Management, LLC; Boston (MA); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Employer-paid health, dental, vision

Wellness benefits

Work-life balance resources

Job summary

RA Capital is seeking an engineer to design and operate AI-enabled data platforms for healthcare data. You’ll work on healthcare data pipelines and AI-driven data access layers where large language models translate user intent into structured, governed queries.

You will bridge enterprise data systems with LLM-based interfaces supporting self-service analytics, discovery, and decision-making. Massachusetts-based, hybrid work is available.

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Science, Information Technology, Software Engineering, or a related field.
• A master’s degree is preferred.
• 1–3+ years of experience in software or data engineering.
• Authorization to work in the United States without sponsorship.
• Based in Massachusetts, able to work in the Boston area, with a hybrid schedule.

Responsibilities

• Design and maintain scalable, production-grade data pipelines for healthcare datasets.
• Build and optimize data models in Databricks to support analytical and AI-driven workloads.
• Develop high-quality Python and SQL code for data standardization, reconciliation, and validation.
• Partner with AI/ML engineers to enable LLM-powered data access.
• Contribute to AI-native data access frameworks.
• Collaborate with healthcare data vendors and internal stakeholders.
• Implement monitoring, validation, and governance for data and AI workflows.
• Document data architectures and AI-enabled pipelines.

Skills

Data engineering

Data modeling

SQL

Python

Java

Spark

LLM-powered systems

APIs (GraphQL)

Education

Bachelor’s degree or higher in CS/DS/IT/SE

Tools

Databricks

Snowflake

Job description

RA Capital is seeking an engineer to design and operate AI-enabled data platforms for healthcare data. You’ll work on healthcare data pipelines and AI-driven data access layers where large language models translate user intent into structured, governed queries.

You will bridge enterprise data systems with LLM-based interfaces supporting self-service analytics, discovery, and decision-making. Massachusetts-based, hybrid work is available.