Staff Software Engineer - AI-Driven Healthcare Platform

Athelas

San Francisco (CA)

On-site

USD 180,000 - 260,000

Full time

2 days ago
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Job summary

Commure seeks an experienced Staff Software Engineer to join our Claims team, building automated workflows that help clinics and hospitals get paid. You’ll work across UI and backend pipelines, own multi-component projects, and design reliable subsystems with clear interfaces.

You’ll mentor peers, lead complex discussions, and deploy production-grade features that improve efficiency and accuracy in revenue cycle management.

Qualifications

  • 10+ years of professional software development experience in production applications.
  • Strong full-stack capabilities with React on the frontend and Python or Go on the backend.
  • Experience designing production subsystems, with reliable interfaces and evolution.
  • Ability to balance speed, correctness, performance, and compliance.
  • Proven track record leading complex work from definition to delivery and operation.

Responsibilities

  • Build fast, scalable claims workflows and user interfaces.
  • Design and implement full-stack features with React, TypeScript, Python, and PostgreSQL.
  • Develop and scale generation and submission pipelines for electronic claims.
  • Integrate with clearinghouses and handle varied payer responses.
  • Lead technical discussions and mentor engineers across the team.
  • Deliver reliable subsystems with clear interfaces and maintainable code.

Skills

React
Python
Go
TypeScript
PostgreSQL
Full-stack
Code reviews
Mentoring
System design
Observability

Tools

CI/CD
Containers
Observability tools

Job description

Commure seeks an experienced Staff Software Engineer to join our Claims team, building automated workflows that help clinics and hospitals get paid. You’ll work across UI and backend pipelines, own multi-component projects, and design reliable subsystems with clear interfaces.

You’ll mentor peers, lead complex discussions, and deploy production-grade features that improve efficiency and accuracy in revenue cycle management.

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