Hire Python
Developers
Backend APIs, data pipelines, ML backends, and AI integrations — written the way Python should be in production: typed, tested, and ready to maintain. US, UK & EU companies, served from India.
What our Python developers build for you
Python is the backbone of most modern AI and data products. Here's what our developers build — and what production-grade means in each area.
Backend APIs (FastAPI & Django)
REST and async APIs built with FastAPI or Django REST Framework — with proper auth, input validation, error handling, and test coverage. Not just endpoints that work in development.
Data Pipelines & ETL
Ingestion, transformation, and loading pipelines for structured and unstructured data — built to run reliably on a schedule, handle partial failures, and be debuggable when something goes wrong at 3am.
ML Backends & Model Serving
Python backends that wrap, serve, and version your ML models — handling inference requests, batch scoring, model switching, and the monitoring that tells you when a model starts to drift.
Task Queues & Background Processing
Celery, RQ, or cloud-native task queues for workloads that shouldn't block an API response — email delivery, report generation, heavy computation, or anything that takes longer than 200ms.
Third-Party API Integrations
Connecting your system to Stripe, Twilio, Slack, Salesforce, or any other external service — with proper auth flow, webhook handling, retry logic, and rate limit management.
Python for AI & LLM Applications
Python developers who understand the AI stack — LangChain, LlamaIndex, Hugging Face, OpenAI SDK — and can build the backend layer behind an AI product, not just consume the API.
Hire Python developers the way you build
Staff Augmentation
Python depth added to your team
A Python developer embedded in your engineering team — taking ownership of the backend layer, data pipelines, or AI integration work your existing team doesn't have capacity or experience for.
Best for
Teams that need Python specialisation added to existing full-stack or frontend-heavy engineering.
Dedicated Python Pod
Backend built end-to-end
A Python developer plus data or AI engineer working as a unit — API layer, data infrastructure, and AI backend all built in one coordinated engagement without handoff problems.
Best for
Companies building a data-heavy or AI-powered product that needs a Python-first backend.
Project-Based
Scoped Python build
A defined-scope engagement: a specific API, a data pipeline migration, an ML serving layer, or a third-party integration. Deliverables and timeline agreed before work starts.
Best for
Well-scoped Python problems with a clear definition of done.
Technologies our Python developers work with
Python
FastAPI
Django
LangChain
LlamaIndex
PyTorch
TensorFlow
Hugging Face
MLflow
AWS
GCP Vertex AI
Azure ML
Docker
SQL
PostgreSQL
Redis
Celery
GraphQLWhy global companies hire Python developers through Artinoid
Python developers are easy to find. Python developers who write typed, tested, async-capable code and understand the AI stack are not. We hire from the second group.
Production Python, Not Notebook Python
Python written for a notebook and Python written for a production API are different things. Our developers write typed, tested, async-aware Python with proper error handling, logging, and deployment configuration — not scripts that work on one developer's laptop.
Faster Than In-House Hiring
Python developers are common. Python developers who understand async, data pipelines, and the AI stack are less so. We've already filtered for the latter. You get matched in days, not months.
40–60% Lower Than US/UK Rates
Senior Python engineering out of India at a fraction of US or UK market rates. Python expertise is deep in India's engineering talent pool — we hire from the top of it.
No Lock-In
Weekly billing, two weeks' notice. Scale up for a build sprint, scale back when it's done, or keep one Python developer on retainer for ongoing backend work. No 12-month commitments.
Simple process, faster than in-house hiring
Discovery Call
We learn about your goals, team structure, timeline, and what a successful engagement looks like for you.
Candidate Matching
We shortlist pre-vetted candidates whose skills and experience closely match your requirements.
Technical Interview
You interview shortlisted candidates directly — same process as in-house hiring. You decide who joins.
Contracts & NDA
Agreements signed swiftly. IP assignment, confidentiality, and data handling are all covered before work begins.
Onboarding
Your new team member is set up, briefed, and contributing from day one. No extended ramp-up.
Common questions
FastAPI vs Django — when do you use each?
FastAPI for modern async APIs where performance and automatic OpenAPI documentation matter, especially for ML model serving and AI backends. Django (with DRF) when you need the admin panel, ORM migrations, and a batteries-included approach — typically for larger web applications with complex data models. Flask when the project is small and neither of the above is worth the overhead. We'll recommend based on your actual requirements, not habit.
Can your Python developers work with our existing codebase?
Yes. Most Python engagements involve inheriting an existing codebase — usually one with inconsistent code style, missing tests, and a setup.py from 2018. We read the code before the first call and bill from productive work, not ramp-up.
Do your Python developers understand the AI/ML stack?
Our Python developers who work on AI projects understand LangChain, LlamaIndex, Hugging Face, OpenAI SDK, and the standard ML libraries (PyTorch, scikit-learn). They build the backend layer behind the model — not the model itself. If you need fine-tuning or eval pipeline work, that's a different specialist we can also provide.
Can you build data pipelines that run reliably on a schedule?
Yes. Data pipelines that only work when a developer is watching are a common problem. We build with idempotency, partial failure handling, dead-letter queues for failed records, observability (Datadog, CloudWatch, or structured logging), and alerting so you know what broke before users do.
How do you handle testing in Python projects?
pytest, with a coverage target agreed at the start of the engagement (not bolted on at the end). Unit tests for business logic, integration tests for database and API calls, and a CI pipeline that runs on every pull request. We also write tests for the code we inherit — not just the code we write.
Can you migrate our legacy Python 2 / Flask codebase?
Yes. Migrations are scoped as a separate engagement — we assess the existing codebase, propose a migration strategy (usually incremental rather than big-bang rewrite), and deliver a plan with estimated effort before work starts. Python 2 is end-of-life; it's worth fixing.
Do your Python developers sign NDAs before project details are shared?
Yes. NDA and IP assignment agreements are signed before any proprietary code, architecture, or business logic is discussed. Standard for every engagement.
Ready to hire Python developers?
Tell us what you're building — API, data pipeline, ML backend, or AI integration. Include your current stack and what production looks like for your use case.
contact@artinoid.com
Response Time
Within 24 hours
Next Step
Discovery call to scope your Python development needs