Full Stack Engineering Intern (Summer 2026)

At Ember, we’re building the future of healthcare operations.

Behind every provider is a mountain of administrative complexity — from billing to revenue cycle management — and these inefficiencies directly impact care, cost, and outcomes. At Ember, we’re simplifying the back office of healthcare through intelligent automation, helping providers focus on what matters most: their patients.

We're reimagining how revenue flows through healthcare, and how teams can scale efficiently without sacrificing quality. Our platform integrates seamlessly into provider workflows, reducing the burden of manual tasks and unlocking real-time visibility into financial and operational performance.

As we grow, we’re looking for passionate, curious people to join us — and right now, that starts with you.

About the role

Skills: Node.js, Python, React, TypeScript

What You’ll Do

• Lead the design and implementation of end-to-end features across our web applications and backend services.
• Build internal evaluation infrastructure for ML and LLM healthcare applications.
• Architect and maintain scalable, secure, and reliable systems that integrate with various healthcare platforms.
• Drive best practices in software development, including code reviews, testing, and documentation.

Qualifications

• Currently pursuing a Bachelor's or Master’s degree in Computer Science, Software Engineering, or a related technical field.
• Proficiency in TypeScript, React, Node.js, and Python.
• Comfortable with LLM applications and containerized deployments.
• Thrives in environments of complexity and ambiguity, prioritizing collaboration and seeking the best ideas regardless of their source.
• A willingness to pitch in wherever needed—we move fast, and we need team players who are eager to contribute.

Bonus

• Hands-on work with LLM prompt engineering, finetuning, and RAG applications.
• Experience with workflow automations.
• Prior work in healthcare, clinical AI, or other regulated, high-stakes industries.
• Open-source contributions to ML libraries, evaluation suites, or benchmarking tools.
• Experience with cloud platforms (e.g., Azure, GCP, AWS) and containerization technologies (e.g., Docker, Kubernetes).
• Strong understanding of database systems, both relational and non-relational.
• Familiarity with healthcare standards such as FHIR, HL7, and medical coding.