Moshe Praver

About Moshe Praver

I’m an MD-turned-engineer with five years of clinical training in Neurosurgery and Radiology, focused on building scalable technology that improves clinical workflows and patient care. My career began at Columbia P&S and expanded into healthtech when I founded a venture-backed telemedicine startup, raised $2M, and brought two digital health products from concept to launch.Currently, I’m a Senior Software Engineer in Generative AI at Abridge, where I build and ship production LLM workflows for real-time clinical notes, including agentic tool use, retrieval, structured outputs, guardrails, and low-latency deployments with strong observability. I design and maintain rigorous evaluation pipelines involving datasets, automated and human-in-the-loop testing, failure-mode probes, and A/B experiments while managing context, latency, and cost.Previously, as an SDE at Amazon (AWS and Amazon Ads), I worked on large-scale, customer-facing systems built on cloud-native, big data architectures. I led and contributed to exabyte-scale initiatives to improve performance, reliability, and user experience for millions of users. Across roles, my focus is on translating clinical and business requirements into safe, reliable, and user-centric AI products.Core ExpertiseLLMs & Generative AI for Healthcare | HealthTech & Digital Health | Product Strategy | User-Centric DesignDistributed Systems & Microservices | Big Data & Analytics | Cloud ArchitectureFDA & HIPAA Compliance | Regulatory NavigationAgile Execution | Cross-functional Collaboration | Roadmapping & Delivery

Experience

1. Senior Software Engineer, Gen Ai

   Abridge

   Oct 2025 — Present · Chicago, IL, US

   Ship production LLM workflows for real-time clinical notes: agentic tool-use, retrieval, structured outputs, guardrails, low-latency deployment, observability.Build rigorous evals: datasets, automated + HIL testing, failure-mode probes, A/B tests, multilingual accuracy; convert clinician feedback into improvements.Partner with clinicians/researchers; integrate with EMRs and Linked Evidence; prototype frontier models while managing context, latency, and cost.

Education

• University of Toronto

  Bachelor of Science - BS

  2006 — 2010

• Columbia University Vagelos College of Physicians and Surgeons

  Doctor of Medicine (M.D.), Medicine

  2010 — 2015