Software Engineer, GenAI
Abridge - SF Office, San Francisco, California, USA, NYC Office
Posted Mar 4, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Assessment
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- Deadline
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Where they hire
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About this role
Software Engineer, GenAI SF Office, San Francisco, California, USA, NYC Office About Abridge Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most-their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. The Role We are looking for GenAI Software Engineers of all levels who are passionate about making a positive impact. You'll collaborate closely with a cross-functional team of researchers, clinicians, and engineers to translate cutting-edge language model capabilities into dependable, real-world clinical systems. Your focus will be on designing advanced LLM-driven workflows that can reason through complex clinical contexts, leverage agentic capabilities and structured tool use, navigate branching chains of LLM calls, integrate seamlessly with retrieval systems, and consistently generate outputs that meet the highest standards
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