Tennr is looking to solve the problem of inefficient provider-provider communication in the healthcare industry, currently relying on faxes and manual data entry, by building intelligent systems using LLMs, vision models, and structured automation.
Requirements
- Proficiency in full-stack development, with a strong understanding of web frameworks, backend systems, and cloud infrastructure
- A track record of working through the full lifecycle of building, testing, deploying, scaling, and monitoring LLM-centered software architectures.
- Understanding of how to test AI system performance beyond raw model accuracy.
- Experience with LLMs, vision models, and structured automation
Responsibilities
- Ship full-stack AI systems end-to-end
- Build observability and debugging tools to capture model performance, user feedback, and long tail cases in production.
- Go from ideation to code within hours; iterate quickly on experiments and data.
- Work directly with ML, Sales, Customer Success, and Implementations to build AI systems for different use cases
Other
- Must articulate ideas well! A big part of making successful AI systems is telling people about them. This includes writing docs and technical reports at the minimum – and speaking in front of an audience at the extreme (optional).
- Experience in healthcare or working with unstructured documents is a plus.
- Ability to work directly with ML, Sales, Customer Success, and Implementations teams
