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Data Engineer

Rad AI


Job Location:

San Francisco, CA - USA

Yearly Salary: USD 145000 - 200000
Posted: 4 September 2026 (11 hours ago)
Application Deadline: 2 December 2026
Vacancies: 1 Vacancy

Department:

Engineering

Job Summary

About Rad AI

At Rad AI were on a mission to transform healthcare with artificial intelligence. Founded by a radiologist our AI-driven solutions are revolutionizing radiologysaving time reducing burnout and improving patient care. With one of the largest proprietary radiology report datasets in the world our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.

Rad AI has secured over $140M in funding including a recently oversubscribed Series C ($68M round) led by Transformation Capital bringing our valuation to $528M. Our investors include Khosla Ventures World Innovation Lab Gradient Ventures Cone Health Ventures and othersall backing our mission to empower physicians with cutting-edge AI.

Our latest advancements in generative AI are used by thousands of radiologists daily supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health Jefferson Einstein Health Geisinger Guthrie Healthcare System and Henry Ford Health.

Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie and ranked by Deloitte as the 19th fastest-growing company in North America we are building AI-powered solutions that make a real impact. Most recently Rad AI was named to CNBCs Disruptor 50 list highlighting the innovation and momentum behind our mission.

If youre ready to shape the future of healthcare wed love to have you on our team!

Why Join Us:

We are seeking a Senior Data Engineer to join our engineering team. With our rapid client growth and ambitious plans for the year ahead we are expanding the team and looking for a skilled professional to play a key role in building and maintaining data platform pipelines and management tools.

What Youll Be Doing:

  • Design and implement the data architecture ensuring scalability flexibility and efficiency using pipeline authoring tools like Apache Airflow AWS Glue and large-scale data processing technologies like Spark.

  • Define and extend our internal standards for style maintenance and best practices for a high-scale data platform.

  • Collaborate with researchers and other stakeholders to understand their data needs including model training and production monitoring systems and develop solutions that meet those requirements.

  • Take ownership of key data engineering projects and work independently to design develop and maintain high-quality data solutions.

  • Ensure data quality integrity and security by implementing robust data validation monitoring and access controls.

  • Evaluate and recommend data technologies and tools to improve the efficiency and effectiveness of the data engineering process.

Who Were Looking For:

  • 5 years relevant experience in data engineering.

  • Expertise in designing and developing distributed data pipelines using big data technologies on large scale data sets.

  • Deep and hands-on experience designing planning productionizing maintaining and documenting reliable and scalable data infrastructure and data products in complex environments.

  • Experience with various database technologies including SQL NoSQL databases (e.g. AWS DynamoDB ElasticSearch Postgresql).

  • Designed built and maintained data infrastructure using IaC like Terraform.

  • Prior Software Engineering experience is a plus.

Nice to Haves:

  • Experience working at an early stage startup.

  • Experience in a HIPAA compliant environment.

  • Experience working on machine learning or healthcare related projects.

Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient caremaking a meaningful impact on millions of lives. Driven by our mission we prioritize transparency inclusion and close collaboration bringing together exceptional people to revolutionize healthcare. If youre passionate about driving innovation and delivering impactful healthcare solutions wed love to hear from you!

To learn more about what its like to work at Rad AI visit and be sure to follow us on LinkedIn to stay up to date!


Location Details:

For roles listed as San Francisco - Onsite:

  • This role will be based in our San Francisco office and we expect employees to work onsite four days per week. The remaining time may be worked remotely or onsite depending on team and business needs.

For roles listed as United States - Remote:

  • This role is open to candidates located anywhere in the United States.

For roles listed as San Francisco - Onsite United States - Remote:

  • We will prioritize candidates who can work onsite four days per week in San Francisco while also considering remote candidates located anywhere in the United States.


For US-Based Full-Time Roles Rad AI offers a variety of benefits including:

  • 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

  • For roles based outside the US your recruiter can share more details

At Rad AI we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race color religion national origin gender sexual orientation age marital status veteran status or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @ or


Required Experience:

IC


About Company

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AI radiology software solutions to streamline workflows, save time, and improve patient care.

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