Abridge
Software Engineer, Intern
About this role
Abridge is seeking Software Engineering Interns for a 3-month Fall 2026 program to build AI-powered clinical features that transform medical conversations into structured notes. You'll work on end-to-end feature development, LLM orchestration workflows, and evaluation frameworks while collaborating across engineering, product, and ML teams with dedicated mentorship.
What you'll do
- Design and build end-to-end features for agentic LLM workflows including retrieval pipelines and tool use
- Fix user-facing bugs and implement quality-of-life improvements across backend and frontend systems
- Develop and work with evaluation frameworks measuring accuracy, robustness, and clinical reliability
- Prototype with new language models, prompting techniques, and orchestration tools like LangChain and LlamaIndex
- Collaborate with cross-functional teams including design, product, ML, and infrastructure to ship customer-facing features
- Build user-centric empathy for clinicians and understand their workflow challenges
What they're looking for
- Full-stack software engineering (backend and frontend development)
- AI and language model orchestration tools (LangChain, LlamaIndex)
- AI-assisted development and responsible AI evaluation
- System design and debugging
- Cross-functional collaboration and communication
- Python or similar backend programming languages
- Quick learning and adaptability in fast-paced environments
Benefits
- Mentorship from experienced software engineers
- Opportunity for full-time return offer for high performers in 2027
- Work on mission-critical healthcare AI technology
- Relocation support to SF or NYC office
- Learning opportunities in generative AI and healthcare
- Collaborative, low-ego team culture with emphasis on growth
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Abridge
Abridge builds an AI platform that transforms healthcare conversations into clinical documentation using advanced natural language processing and generative AI. The company is hiring ML infrastructure engineers, implementation engineers, and machine learning scientists to develop model serving systems, manage customer deployments, and advance medical NLP research.
- Website
- abridge.com
Likely interview questions
- Tell us about a time you used AI tools to accelerate your development—how did you know when to trust the output versus verify it manually?
- Describe your experience building or integrating with language models or LLM frameworks like LangChain or LlamaIndex.