Python jobs in the United States
This board is scoped to Python as web and backend work rather than Python as the language data science happens to use. That distinction matters in the American market more than anywhere else, because the same word on a posting can mean a Django service handling payments or a research role that never ships an endpoint.
- Open roles
- 57
- Companies hiring
- 49
- Fully remote
- 12
- Pay published by the employer
- 23 of 57
- Senior Python Engineer - LLM Code Evaluation
- Sr. Software Engineer - Wallet - Authentication
- Full Stack Developer
- Sr. Python Backend Engineer
- Sr. Full-Stack Engineer, Product
- Senior Software Engineer, Backend
- AI Engineer
- Sr. Software Engineer - AI-First
- AI Software Engineer
- Integration Engineer II with API and Integration Tool Experience
- Senior Backend Software Engineer
- Full Stack Software Engineer
- Integration Engineer II with API and Integration Tool Experience
- Full Stack Engineer - Python - W2 position
- Software Engineer, Agents
- Engineering Manager
- DAC AI engineer
- Product Tech Lead
- Senior Software Engineer, Full Stack - Sales Planning
- Staff Software Engineer, Billing Agents
- Staff Software Engineer, Billing Agents
- Sr. Software Engineer
- Senior Software Engineer I, Full Stack
- Forward Deployed Engineer
- Senior Software Engineer, Full-Stack
What the backend Python roles look like
Django and FastAPI carry most of them, sitting in front of Postgres, with Celery or a similar worker doing anything slow. The employers skew toward product companies and health, education and fintech operators rather than the banks that dominate Java hiring here. Team sizes are smaller and the scope per engineer is usually wider.
Telling it apart from the AI roles
If a posting spends its first paragraph on models, training or inference, it belongs on the AI engineering board and will usually be found there instead. The split is deliberate: a reader looking for someone to own an API has a different job in mind than a reader looking for someone to improve a model, and mixing the two wastes everybody's time.