Python

Hire senior Python developers

Django, FastAPI, data engineering, and AI/ML - our Python engineers handle the full spectrum. Production backends, not Jupyter notebooks.

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Sound familiar?

  • •You need Python engineers who can build production APIs with FastAPI or Django - not just Jupyter notebook prototypes that fall apart under real traffic
  • •Your data pipelines are fragile scripts held together with cron jobs - no monitoring, no retry logic, no alerting when things break
  • •AI/ML model integration keeps getting delayed because your web team doesn't understand model serving, embeddings, or vector databases
  • •Hiring senior Python developers in the US costs $170K+ and takes months - meanwhile your roadmap keeps slipping

What our Python engineers deliver

Backend and data engineers who build systems that handle real production workloads.

FastAPI & Django backends

Production APIs with FastAPI's async performance or Django's batteries-included approach. Proper request validation with Pydantic, automatic OpenAPI docs, background tasks, and middleware pipelines that handle real-world complexity.

AI/ML integration

We bridge the gap between data science and production engineering. Model serving with FastAPI, LLM integrations with LangChain, RAG pipelines with vector databases, and inference optimization for production latency requirements.

Data engineering

ETL pipelines with Apache Airflow, data transformation with Pandas and Polars, and data warehouse integrations. Pipelines that process millions of records with proper error handling, monitoring, and incremental loading.

Async & task processing

Celery workers for background jobs, asyncio for concurrent I/O, and distributed task queues with Redis or RabbitMQ. Long-running processes that don't block your API and retry gracefully on failure.

Security & validation

Input validation with Pydantic, SQL injection prevention with SQLAlchemy, proper authentication with OAuth2 and JWT, rate limiting, and CORS configuration. Security patterns baked into every endpoint.

Testing & observability

pytest with fixtures and parametrized tests, coverage reporting, structured logging with structlog, and APM integration with Datadog or New Relic. Debug production issues in minutes, not hours.

What teams build with us

REST API backends

High-performance APIs with FastAPI serving millions of requests. Proper versioning, pagination, filtering, and caching strategies. OpenAPI documentation generated automatically from your code.

Machine learning services

Model serving endpoints, feature stores, prediction APIs, and ML pipeline orchestration. We deploy models behind production APIs with proper batching, caching, and fallback strategies.

Data pipelines & ETL

Airflow DAGs, custom ETL scripts, and data warehouse loading. Ingest data from APIs, databases, and file systems with proper schema validation, deduplication, and incremental processing.

AI-powered applications

Chatbots with LangChain, document intelligence with embeddings, content generation pipelines, and recommendation engines. Production AI features that go beyond proof-of-concept demos.

The tech stack our engineers use daily

Production-tested Python tools and frameworks.

FastAPI

Async APIs

Django

Full-stack framework

SQLAlchemy

ORM & queries

Celery

Task processing

Pandas / Polars

Data processing

LangChain

LLM integration

pytest

Testing

Docker / AWS

Deployment

Frequently asked questions

Do your Python developers have AI/ML experience?
Yes. Our Python team includes engineers with production experience in LLM integrations, RAG pipelines, model serving, and data engineering. They can build the API layer around your ML models and deploy them to production with proper monitoring.
FastAPI or Django - which do you recommend?
FastAPI for high-performance APIs, microservices, and AI/ML backends where async performance matters. Django for full-stack applications with admin panels, ORM, and built-in auth. We'll recommend the right choice based on your project requirements.
Can you help migrate from Flask to FastAPI?
Yes. We've migrated several Flask applications to FastAPI. The process includes converting route handlers, adding Pydantic models for validation, implementing dependency injection, and setting up async database connections.
How do you handle Python dependency management?
We use Poetry or pip-tools for deterministic dependency resolution with locked versions. Virtual environments, Docker containers, and CI pipelines ensure consistent environments across development, staging, and production.

Ready to hire Python developers?

Tell us about your project and we'll match you with senior Python engineers within a week.

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