Python for data processing, AI integrations, and backend services.
Python is the right tool for specific problems: data processing, ML inference, scientific computation, and scripting. When the project requires Python — data pipelines, AI feature integration, or a Python-first backend — finding a developer with production Python experience matters.
Need a Python developer for a data pipeline, AI integration, backend API, or Python-specific service
Python has legitimate use cases in web development:
AI/ML integrations: OpenAI, Anthropic, and most ML frameworks have first-class Python SDKs. Building AI features — RAG pipelines, inference services, embeddings — often happens in Python first, then wrapped in an API.
Data processing: Pandas, Polars, NumPy for large-scale data transformation. When processing millions of rows of CSV or running complex aggregations, Python has a mature ecosystem.
FastAPI for APIs: FastAPI is a modern Python web framework with automatic OpenAPI documentation, Pydantic for request validation, and async support. Good for Python-first teams or services that need tight integration with Python data libraries.
When not to use Python: Standard web application with no data/AI requirements: use TypeScript/Next.js. The operational simplicity of a single language stack (TypeScript everywhere) outweighs Python's advantages unless the specific use case requires it.
Python production requirements: Type hints with mypy (Python's version of TypeScript). Async with FastAPI or async SQLAlchemy. Docker for deployment. Dependency management with Poetry or uv.
Python service or application with proper async handling, type hints, and production deployment
FastAPI service
with Pydantic validation
Data pipeline
with Pandas/Polars
AI integration
(OpenAI API, embeddings, RAG)
Async background workers
for data processing
Docker deployment
to Fly.io or Railway
One honest number to start.
Fixed-scope, fixed-price. The number below is the starting point — final scope is built from your brief.
Python service or application with proper async handling, type hints, and production deployment
Three steps, every time.
The same repeatable engagement on every project. No surprises, no mystery, no billable ambiguity.
Brief & discovery.
We send you questions, then get on a call. Output: a written scope with every step, feature, and integration listed.
Build & ship.
Fixed schedule, weekly reviews. No scope creep unless you change the scope — and if you do, we reprice it transparently.
Warranty & retainer.
30-day warranty on every launch. Most clients stay on a monthly retainer for ongoing features and maintenance.
Why Fixed-Price Matters Here
Python service scope is the data model, processing requirements, and API surface. Fixed-price.
Questions, answered.
TypeScript: if the AI integration is a simple API call (OpenAI chat completions) alongside a TypeScript backend. Python: if the AI work involves custom embeddings, model fine-tuning, or heavy use of the Python ML ecosystem.
Tell Ryel about your project.
Describe what you’re building and what outcome you need. You’ll have a written, fixed-price scope within the week.