# Joseph Lee

> AI Software Engineer at Cohere

Location: Huntsville, Texas, United States
Profile: https://flows.cv/josephlee1

🤔 Who am I?
I'm a senior software engineer with over a decade of experience building scalable, cloud-based platforms across enterprise search, healthcare, and applied AI. I combine a strong full-stack background (React, TypeScript, Python, FastAPI) with hands-on work in LLMs, RAG systems, vector search, and model-driven integrations. My recent focus has been applying generative AI in production environments to improve performance, security, and clinical and enterprise workflows. I’m actively expanding my professional network and open to opportunities at the intersection of full-stack engineering and AI/ML product development.

## Work Experience
### AI Software Engineer @ Cohere
Jan 2024 – Jan 2025 | New York City Metropolitan Area
At Cohere, I worked on North, the platform that lets companies build their own AI agents using Cohere’s LLMs. I helped turn complex retrieval and model workflows into practical tools that teams could deploy, monitor, and scale in real environments. My focus was on making the agent experience more reliable and usable, so enterprises could adopt LLMs without needing deep ML expertise.

### Senior Full-Stack Engineer (AI + Healthcare) @ Abridge
Jan 2022 – Jan 2023 | New York, New York, United States
At Abridge, I contributed to building Linked Evidence, a clinical AI platform that maps AI-generated summaries back to source audio and transcripts to improve trust and transparency in clinician workflows. I delivered full-stack features using Python, FastAPI, React, and TypeScript, developed secure FHIR/REST integrations with hospital systems, and scaled inference services for real-time and batch clinical documentation. My work supported enterprise EMR workflows and helped reduce documentation friction through reliable, scalable AI-assisted tooling.

### Senior Software Engineer @ Yext
Jan 2013 – Jan 2022 | New York, New York, United States
At Yext, I helped evolve Yext Answers into an NLP-driven enterprise search platform by building backend microservices in Java and Go to support semantic search, indexing, and high-volume data processing for the Knowledge Graph. I developed front-end features in React and TypeScript for enhanced search experiences and internal tooling, and I improved data ingestion and infrastructure reliability using AWS, Docker, and Kubernetes. My contributions helped scale search relevance and performance for large-scale enterprise deployments.


## Education
### Bachelor of Science - BS in Computer Science
Massachusetts Institute of Technology
Jan 2009 – Jan 2013


## Contact & Social
- LinkedIn: https://linkedin.com/in/joseph-lee-41300039b

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Source: https://flows.cv/josephlee1
JSON Resume: https://flows.cv/josephlee1/resume.json
Last updated: 2026-03-29