Rad AI is hiring a Data Engineer for a fully remote, Work From Home role open to candidates anywhere in the United States. If you have been scanning Remote Jobs USA boards for a serious healthcare-AI opportunity, this Data Engineer posting is one of the strongest WFH Jobs available right now, offering $145K–$200K/yr, real equity in a $528M-valuation company, and a mission that touches millions of patients.

About Rad AI & This Remote Jobs USA Opportunity

Rad AI is transforming healthcare with artificial intelligence. Founded by a radiologist, the company’s AI-driven solutions save time, reduce burnout, and improve patient care using one of the largest proprietary radiology report datasets in the world. Rad AI’s technology has helped uncover hundreds of new cancer diagnoses and cut error rates in tens of millions of radiology reports by nearly 50%. With over $140M in funding — including a recently oversubscribed $68M Series C led by Transformation Capital — and a $528M valuation, Rad AI is backed by Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and more. Its generative AI tools are used daily by thousands of radiologists at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health, and the company was recently named to CNBC’s Disruptor 50 list.

Data Engineer Responsibilities

As a Senior Data Engineer, you’ll join Rad AI’s engineering team and play a central role in building and scaling the company’s data platform, pipelines, and management tooling as client growth accelerates.

• Design and implement scalable, flexible data architecture using pipeline tools like Apache Airflow, AWS Glue, and large-scale processing frameworks like Spark
• Define and extend internal standards for style, maintenance, and best practices across a high-scale data platform
• Partner with researchers and stakeholders to understand data needs for model training and production monitoring, then build solutions that meet those requirements
• Own key data engineering projects end-to-end — designing, developing, and maintaining high-quality data solutions independently
• Ensure data quality, integrity, and security through robust validation, monitoring, and access controls
• Evaluate and recommend new data technologies to improve engineering efficiency

Requirements for This Remote Data Engineer Role

• 5+ years of relevant data engineering experience
• Expertise designing and developing distributed data pipelines on large-scale datasets using big data technologies
• Hands-on experience designing, planning, productionizing, maintaining, and documenting reliable, scalable data infrastructure in complex environments
• Experience with SQL and NoSQL databases such as AWS DynamoDB, ElasticSearch, and PostgreSQL
• Experience building and maintaining data infrastructure with Infrastructure-as-Code tools like Terraform
• Prior software engineering experience is a plus

Nice-to-Have Skills

• Experience working at an early-stage startup
• Experience in a HIPAA-compliant environment
• Background on machine learning or healthcare-related projects

Compensation, Benefits & Remote Setup

This Data Engineer, Work From Home role pays $145,000–$200,000/year and is open to candidates anywhere in the United States. Note: this listing is fully remote (United States – Remote); it is not one of Rad AI’s hybrid San Francisco-onsite roles. US-based full-time employees receive:

• Comprehensive Medical, Dental, Vision & Life insurance
• HSA (with employer match), FSA, and DCFSA
• 401(k) retirement plan
• 11 paid company holidays plus a flexible PTO policy
• Annual company-wide offsite and periodic team offsites
• Annual equipment stipend for your home office

How to Apply for This Remote Jobs USA Data Engineer Role

Ready to build the data infrastructure behind AI that’s already helped uncover hundreds of new cancer diagnoses? Apply directly through Rad AI’s careers page below, and explore our full board of Remote Jobs USA and WFH Jobs for more Work from Home Jobs like this one.

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