Hire pre-vetted FastAPI Developers

FastAPI's own documentation claims it lets teams build features 200 to 300 percent faster than a comparable framework and cut developer-induced bugs by about 40 percent. Those numbers hold up when whoever is writing your endpoints actually understands async under load. They fall apart the moment someone drops a blocking database call or a synchronous HTTP request inside an async def handler and stalls the entire event loop, which is the most common way a fast framework quietly ships a slow API.

What Actually Slows FastAPI Projects Down?

Most Python developers can type async def in front of a route and call it done. Whether the code underneath is genuinely non-blocking, whether database sessions are async-safe, and whether connection pools are sized for real concurrency is a narrower skill most generalist hires never had to practice. Cortance's matching screens for exactly that before a CV reaches you: Pydantic validation and serialization, dependency injection patterns, async ORM usage, and OpenAPI documentation discipline are checked during a five-stage vetting process, including identity and CV verification, an English check, a recorded HR interview, and a hands-on technical evaluation built around real engineering problems, not textbook quizzes. As a European outstaffing platform with developers across 35+ countries, Cortance turns an open job post into a shortlist that already cleared that bar, delivered within 30 minutes of your request.

Where Cortance's FastAPI Developers Have Shipped

Our developers' FastAPI portfolio spans fintech data platforms, AI-assisted reporting tools, and real-time marketplaces. Recent work delivered:

1. Fintech market-data APIs. FastAPI services layered over AWS Glue and PySpark pipelines, turning market and fundamental data into structured endpoints backed by PostgreSQL and DocumentDB.
2. AI-powered inspection reporting. An AWS serverless FastAPI backend (Lambda, API Gateway, RDS PostgreSQL) that converts field notes into structured reports for a marine services platform.
3. Multi-agent LLM backend. A FastAPI service layer with async endpoints and structured confidence scoring behind an LLM-based diagnosis pipeline for a veterinary health platform.
4. Real-time bidding infrastructure. WebSocket-based bidding endpoints and fraud-prevention validation logic built with FastAPI for a vehicle auction platform.

The Stack Our FastAPI Developers Bring

Beyond the core framework, our engineers work with Pydantic v2 for validation and serialization, SQLAlchemy 2.0 async and Tortoise ORM for the data layer, and Uvicorn or Gunicorn with Uvicorn workers for production serving. They pair FastAPI with PostgreSQL, Redis, and Docker or Kubernetes for deployment, wire up OAuth2 and JWT authentication, and add Prometheus and Grafana once an API needs real observability instead of a health check endpoint. Automatic OpenAPI and Swagger documentation is a baseline expectation, not a bonus feature someone adds before a demo.

Migrating From Flask or Django? Here's What Actually Changes

Moving an existing Flask or Django REST Framework service to FastAPI is not a drop-in rewrite. Type hints become the validation layer instead of manual serializers, dependency injection replaces decorator-heavy request handling, and the async runtime means blocking libraries that worked fine in a WSGI app need to be swapped for async-safe equivalents. Our developers have handled this migration path directly, not just greenfield FastAPI builds, so a legacy Django API and a new FastAPI service can usually share the same team without a second learning curve.

Whether you need one senior FastAPI engineer to fix a stalled async migration, a small dedicated team to build a new API platform, or staff augmentation to hit a launch date, share your requirements and Cortance will return matched profiles within 30 minutes. Interview with no commitment, hire in as little as 48 hours, and get a free replacement if a match is not the right fit.