Software Engineer, Data/AI

RA Capital Management•Boston, MA

7h•Hybrid

About The Position

RA Capital is seeking an early-career software engineer to join their Data Engineering team. This role focuses on building and operating AI-enabled data platforms and intelligent data workflows for healthcare data. The position involves more than traditional ETL, including developing healthcare data pipelines, AI-driven workflows, and data applications that integrate large language models (LLMs) with enterprise data and tools. Responsibilities include creating governed data access layers where LLMs translate user intent into structured queries, and building agentic workflows for information retrieval, tool invocation, task orchestration, and self-service analytics. The role is situated at the intersection of healthcare data, large-scale data engineering, and applied AI, with a strong emphasis on reliability, compliance, and production readiness.

Requirements

Strong software engineering fundamentals and an interest in building production systems.
Strong foundation in data engineering and data modeling.
Proficiency in Python and SQL.
Experience building or integrating APIs, services, or workflow-oriented applications.
Hands-on experience with, or a strong interest in, LLM-powered applications, AI agents, or agentic workflows.
Familiarity with LLM tool use, structured outputs, orchestration patterns, GraphQL, or other API-based data access methods.
Strong communication, ownership, and collaboration skills.
Bachelor’s degree or higher in Computer Science, Software Engineering, Data Science, or a related technical field, or equivalent practical experience.
Up to three years of experience in software engineering, data engineering, or a related role.
Must be based in the Boston area and available to work a hybrid schedule from our Boston office.
Must be authorized to work in the United States without current or future sponsorship.

Nice To Haves

Experience with Spark and Databricks is preferred.
Experience working with healthcare or other regulated datasets is a plus.
A master’s degree is preferred.

Responsibilities

Design and maintain scalable, production-grade data pipelines for healthcare datasets, including claims and provider data.
Build and optimize data models to support analytical and AI-driven workloads.
Develop high-quality Python and SQL code for data standardization, reconciliation, validation, and application workflows.
Build AI-powered data applications and agentic workflows that connect LLMs with enterprise data and internal tools, retrieve information, execute multi-step tasks, and automate data and research processes with appropriate guardrails.
Build and improve AI-native data access frameworks, including LLM-to-SQL and LLM-to-GraphQL patterns and reusable interfaces for structured data access.
Build backend services, APIs, and reusable software components that power data and AI applications.
Develop evaluation and testing frameworks to measure the accuracy, reliability, and performance of LLM-powered and agentic workflows.
Write automated tests and contribute to CI/CD, deployment, and production support for data and AI systems.
Collaborate with AI/ML engineers, healthcare data vendors, and internal stakeholders to translate user needs into production-ready data and AI solutions.
Implement monitoring, observability, and governance for data pipelines and AI workflows.
Document data architectures, AI-enabled workflows, and production systems.