Job Overview
Location
United States
Job Type
Full-time
Category
Software Engineering
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • Design and implement scalable, flexible, and efficient data architecture using pipeline authoring tools like Metaflow and large-scale data processing technologies such as Spark.
- • Define and extend internal standards for style, maintenance, and best practices for a high-scale data platform.
- • Collaborate with researchers and other stakeholders to understand data needs for model training and production monitoring systems, then develop tailored data solutions.
- • Take ownership of key data engineering projects, designing, developing, and maintaining high-quality data solutions independently.
- • Ensure data quality, integrity, and security by implementing robust data validation, monitoring, and access controls.
- • Evaluate and recommend new data technologies and tools to enhance the efficiency and effectiveness of the data engineering process.
- • Continuously monitor, maintain, and improve the performance and stability of the data infrastructure.
- • Work with big data processing and analytics on AWS, utilizing services such as Amazon EMR and AWS Batch.
- • Develop and maintain distributed data pipelines on large-scale datasets.
- • Design, productionize, maintain, and document reliable and scalable data infrastructure and data products in complex environments.
- • Utilize database technologies including SQL, NoSQL databases (e.g., AWS DynamoDB, Elasticsearch, PostgreSQL).
- • Apply containerization technologies such as Docker and Kubernetes in data pipeline deployments.
- • Support AI-driven healthcare solutions used by thousands of radiologists daily across more than one-third of U.S. radiology groups and healthcare systems.
- • Contribute to a data platform that processes tens of millions of radiology reports, reducing error rates by nearly 50% and uncovering hundreds of new cancer diagnoses.
- • Operate within a high-growth environment with rapid client expansion and ambitious product development goals.
- • Work with one of the largest proprietary radiology report datasets in the world, powering AI solutions adopted by major healthcare systems including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.
🎯 Requirements
- • 5+ years relevant experience in data engineering
- • Expertise in designing and developing distributed data pipelines using big data technologies on large-scale datasets
- • Deep and hands-on experience designing, productionizing, maintaining, and documenting reliable and scalable data infrastructure and data products in complex environments
- • Solid experience with big data processing and analytics on AWS, using services such as Amazon EMR and AWS Batch
- • Experience in large-scale data processing technologies such as Spark
- • Expertise in orchestrating workflows using tools like Metaflow
🏖️ Benefits
- • Comprehensive Medical, Dental, Vision & Life insurance
- • HSA (with employer match), FSA, & DCFSA
- • 401(k)
- • 11 Paid Company Holidays
- • Flexible PTO policy
- • Annual company-wide offsite
- • Periodic team offsites
- • Annual equipment stipend
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Rad AI
Rad AI provides AI-powered radiology workflow software for hospitals and imaging centers. Its platform automates repetitive tasks in radiology reporting, such as follow-up recommendations and incidental findings detection, reducing radiologist burnout and improving patient care. The company’s products integrate with existing PACS and RIS systems to streamline radiology operations. Rad AI serves healthcare systems across the United States.
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