Senior Software Engineer (Air AI)
Posted Updated
- At Commure, our Air AI team is building the intelligence layer that lives inside the clinical workflow, that listens, documents, reasons, and acts so clinicians don’t have to
- You’ll work across documentation that transcribes patient visits and structures them into clinical notes in real-time, a conversational clinical assistant grounded in live patient context and medical literature, and an extensible AI Skills Library of reusable agents and workflows that automates clinical tasks across the platform
- If you want to build AI that clinicians trust with their most critical work, this is that team
- Leverage and build on top of AI/LLM technologies to accelerate product development and deliver intelligent, automated experiences to clinicians and patients
- Design and influence decisions that shape our fullstack architecture for scalable, AI-powered healthcare solutions
- Lead or contribute to technical planning for new features, balancing feasibility, clinical usability, and business impact
- Establish best practices for code quality, testing, deployment, and observability
- Mentor engineers across the team, raising the bar on design patterns, code standards, and technical thinking
- Collaborate with product managers, designers, and clinical experts to ship intuitive solutions that work in real clinical environments
- Be part of a fast-moving team that celebrates large ambition, ships daily, and makes decisions quickly
- Strong communication skills — comfortable working with both engineers and non-technical stakeholders including clinical teams
- Track record of driving work from early ideation to successful production deployment
- Professional software engineering experience, ideally in a high-growth or startup environment
- Experience in fast-moving environments where shipping quickly is the norm
- Strong fullstack skills — Python on the backend (required), TypeScript/React on the frontend, with working knowledge of containers and cloud (Docker, Kubernetes)
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, required
- Hands-on experience integrating LLM APIs or building AI-powered features in production
- Strong debugging and problem-solving skills with a history of demonstrated resourcefulness