Hire senior Django developers for your Python backend

Senior Django engineers from Latin America who build APIs with DRF, tune the ORM, run Celery at scale and work inside your repos on US hours.

By the Ryz Labs team · Updated October 2026

Hiring Django developers through Ryz Labs gets you senior Python engineers who have run Django in production, not just built tutorials with it. They are vetted, top 1% of the engineers we interview, and they embed in your team: same repos, same standups, same review process. They work within an hour of US time zones.

What our Django developers work on

Django sits behind a huge range of systems, from internal admin tools to high-traffic APIs and the backends of AI features. Our Django engineers are strongest where the framework meets real data volume, background processing and integrations with other services.

REST and GraphQL APIs with Django REST Framework, django-ninja or Strawberry, including versioning, pagination and permission classes.
Data-heavy applications on PostgreSQL, using JSONB fields, full-text search, partial indexes and the ORM's aggregation tools.
Background processing with Celery or RQ on Redis or RabbitMQ: scheduled jobs, long-running imports, retries and monitoring with Flower.
Async and real-time features with ASGI, Django Channels and async views where they actually help.
Backends for AI features: Django services that call OpenAI or Anthropic models, store embeddings with pgvector, and expose results to the rest of your product.
Version upgrades from Django 2.x or 3.x to 4.2 LTS and 5.x, including dependency cleanup and Python version moves.
Admin and internal tools built on a customized Django admin, which still saves teams months of work.

Skills we vet for

ORM fluency: select_related versus prefetch_related, Prefetch objects, F and Q expressions, subqueries, annotations, and reading the SQL the ORM generates.
Migrations: writing data migrations, squashing, and running schema changes on large Postgres tables without locking production.
Django REST Framework: serializers that do not hide N+1 queries, viewsets, throttling, custom authentication and permission logic.
Celery: idempotent tasks, acks_late, visibility timeouts, chords and chains, and how to avoid sending model instances through the broker.
Transactions and concurrency: atomic blocks, select_for_update, transaction.on_commit, and race conditions in signup or payment flows.
Testing: pytest-django, factory_boy, test isolation, and keeping a test suite fast as it grows.
Security: Django's CSRF and XSS protections, safe use of raw and extra, settings hardening, and secrets management.
Deployment: Gunicorn or Uvicorn workers, Docker, static files with WhiteNoise or a CDN, and observability with Sentry and structured logs.

How we vet Django developers

Recruiters source Django engineers with production experience across Latin America. ARC, our in-house ranking system, sorts that pipeline so the strongest profiles get attention first. Each candidate goes through a structured NTRVSTA AI interview focused on Python and Django, and recruiters review them before and after it. You receive a curated shortlist. AI scores inform the process, but they are advisory. People make the decisions, and you meet candidates before anyone starts.

Sample interview topics

A DRF list endpoint fires 400 queries per request. Walk through finding the cause with django-debug-toolbar or query logging, then fix it with select_related, prefetch_related and a custom Prefetch queryset.
You need to add a non-null column with a default to a Postgres table with 80 million rows. How do you write the migration so it does not lock the table, and how does this differ across Postgres versions?
A Celery task sends a welcome email right after a user is created, but sometimes the user does not exist yet when the task runs. Why, and how does transaction.on_commit fix it?
Two requests try to redeem the same coupon at once. Show how you would prevent double redemption using select_for_update, a unique constraint, or both, and explain the trade-offs.
When would you use async views in Django, and when do they make things worse? Discuss sync_to_async, database connections under ASGI, and what the ORM supports asynchronously today.

Ways to hire Django developers

Option	Best for	Trade-offs
Freelance marketplace	Small, well-defined Django tasks with a clear end	You screen every applicant yourself; limited continuity once the gig ends
Staffing or recruiting agency	Hiring a permanent Django engineer onto your payroll	Technical screening is often shallow; placement fees; long search for senior people
In-house recruiting	Core long-term roles with deep company context	Slow and costly; competes with every other Python employer for the same people
Ryz Labs staff augmentation	Adding senior Django engineers to an existing product team	Custom quote, scoped per team; you set priorities and own the roadmap
Ryz Labs AI pod team	Building AI systems on a Python and Django backend inside your cloud	A dedicated multi-person pod; best when you have a defined AI initiative to staff

Ryz is not the right fit if you want short hourly gigs through a self-serve marketplace or a trial before talking to anyone. It is also not the right choice if you need published pricing up front or engineers in European time zones.

Why hire Django developers from Latin America

Python is one of the most taught languages in Latin American universities, and Django has an active community there, with PyCon and DjangoGirls events across Brazil, Argentina, Colombia and beyond. Many senior engineers in the region have spent years on Django codebases for US companies, which means they already know the habits of US product teams.

Time zones matter for backend work in particular. A migration plan, a production incident or a pull request on a shared data model goes better when both sides are online. Our engineers work within an hour of US hours, so those conversations happen in real time.

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FAQ

Do your Django developers also handle front-end work?

Some do. Many of our Django engineers pair it with React, Vue or HTMX. If you need one person across the stack, tell us and we shortlist full-stack profiles.

Can a Django developer help build AI features into our product?

Yes. Our Django engineers regularly build the backend side of AI features: model calls, retrieval with pgvector, background jobs and APIs. For a larger AI initiative, an AI pod team gives you a dedicated group with ML and backend engineers together.

What does it cost?

Pricing is a custom quote, scoped per team. You get a plan, a price and the names of the engineers who would do the work before you sign.

Who do I contract with, and will they overlap with my team?

You sign one contract with Ryz. Our engineers work with us as independent contractors, and we handle paying them. They keep hours within an hour of US time zones and join your standups.

Questions we didn't answer? Email info@ryzlabs.com.