About the role
The Python Developer role consists of building the backends Python dominates: REST and async APIs, data-heavy services, integrations, and the server side of AI features. Python's superpower is range — the same senior can ship a FastAPI service on Monday and a data pipeline on Thursday — which is why it became the default language of AI-era backends.
Monthly rate
$4,500–$7,000/mo
All-in: contract, benefits, equipment, IP
Experience
10+ years typical
Location
Latin America
Argentina · Colombia · Mexico · Chile
Timezone
Full US overlap
Fluent English, onboarded in one week
Core stack
AI tools, daily
Verticals seen
What they own — and what they don't
What they own
- Design and build APIs and services in Django, FastAPI, or Flask
- Own data-heavy backend work: pipelines, integrations, background jobs
- Build the server side of AI features — the natural home of LLM tooling
- Keep performance honest: profiling, async patterns, query tuning
What they don't — and who does instead
- Frontend work beyond the API contract — that's a frontend or full-stack hire
- Train custom models — that's an ML Engineer, though they speak the same language
- Own cloud infrastructure — that's DevOps
Who hires this role, and for what
Product teams whose backend is Python. The roadmap outgrew the team, and senior Python hiring in the US is slow and expensive.
Companies building AI features. The LLM ecosystem is Python-first — a senior Python backend engineer is the shortest path from prototype to production API.
Data-heavy businesses. When the product is built on moving and transforming data, Python seniors carry both the service layer and the pipelines.
- 01
API platform build-out. Django or FastAPI services designed for the load you actually have, and the load you're planning for.
- 02
AI feature backends. The service layer behind LLM features — orchestration, caching, rate limits, cost control.
- 03
Integration work. Third-party APIs, webhooks, and internal systems stitched into one reliable flow.
- 04
Legacy Python modernization. Python 2-era codebases and tangled Django monoliths brought to modern, testable shape.
Work our engineers at this role have shipped
- FastAPI backend for a multi-tenant agentic platform in regulated finance
- Django service layer consolidating three acquired products into one API
- High-volume ETL and reporting pipeline feeding a customer-facing analytics product
Do you actually need a Python Developer?
You do, if:
- Your backend is Python and your seniors are stretched thin
- An AI feature needs a production-grade Python service behind it
- Data work and API work keep competing for the same one person
You probably don't, if:
- The core need is training models, not serving them — see ML Engineer
- Your stack is Node/TypeScript end to end — hire in your own ecosystem
Not sure which role fits? Tell us the problem instead of the title — we'll tell you what we'd actually staff, even if it's not this. If it is this: discovery call today, matched profiles in 48 hours, onboarded in a week.
Hire a Senior Python Developer