Partner with experienced FastAPI developers, engineers, architects, and specialists who deliver scalable, high-performance API solutions. Leading enterprises and innovative startups hire FastAPI developers from us to build modern RESTful APIs, microservices, backend systems, real-time data pipelines, and robust integrations while optimizing performance, security, and developer workflows.
Discover why leading companies worldwide choose FastAPI for building high-performance, scalable APIs and microservices with modern Python development.
Utilizes FastAPI for building high-performance APIs to handle real-time ride requests and driver matching.
Enhances scalability and reduces latency in their microservices architecture.
FastAPI powers critical backend services, improving ride-hailing efficiency.
Implements FastAPI to serve machine learning models for personalized content recommendations.
Accelerates model inference times, delivering real-time suggestions to users.
FastAPI-based endpoints facilitate rapid content personalization.
Adopts FastAPI for developing APIs that integrate with Azure services and machine learning pipelines.
Streamlines API development, enhancing cloud service offerings.
FastAPI supports scalable backend services on Azure.
Employs FastAPI to build APIs for travel booking and itinerary management.
Improves response times and system reliability for global travel operations.
FastAPI enables efficient handling of booking requests.
Leverages FastAPI for financial data processing and automation tools.
Enhances the speed and reliability of financial operations.
FastAPI powers backend services for financial automation.
Uses FastAPI to develop APIs for corporate travel management solutions.
Provides fast and reliable services to corporate clients.
FastAPI supports backend services for travel booking and management.
Implements FastAPI to build APIs for e-commerce logistics and shipping solutions.
Streamlines logistics operations, improving delivery times.
FastAPI facilitates real-time shipping updates for e-commerce platforms.
Adopts FastAPI for telemedicine services, including appointment scheduling and patient management.
Provides secure and efficient healthcare services online.
FastAPI supports backend services for telehealth applications.
Recommends FastAPI for deploying machine learning models and building APIs within Azure.
Simplifies API development and deployment in the cloud.
FastAPI is integrated into Azure's machine learning ecosystem.
Supports FastAPI for building serverless APIs using AWS Lambda and API Gateway.
Enables scalable and cost-effective API solutions.
FastAPI is utilized in serverless architectures on AWS.
Facilitates FastAPI deployment on Google Cloud Run and Kubernetes Engine.
Provides scalable and managed API hosting solutions.
FastAPI is deployed in containerized environments on Google Cloud.
Incorporates FastAPI in building APIs for AI and data analytics services.
Enhances the performance and scalability of data-driven applications.
FastAPI supports backend services for AI analytics platforms.
Utilizes FastAPI for backend services related to music recommendation systems.
Improves the speed and accuracy of music recommendations.
FastAPI powers APIs for personalized music suggestions.
Implements FastAPI to build APIs for payment processing and financial services.
Enhances the performance and reliability of payment systems.
FastAPI supports backend services for payment gateways.
Uses FastAPI to develop APIs for real-time messaging and collaboration tools.
Provides fast and reliable communication services to users.
FastAPI powers backend services for messaging platforms.
FastAPI is built on top of Starlette (ASGI) and uses Pydantic for data modelling, letting it handle asynchronous tasks and concurrent requests efficiently. It often outperforms traditional synchronous Python frameworks like Flask and Django in I/O-bound workloads.
Thanks to Python's type hints and built-in data validation, automatic generation of OpenAPI/Swagger documentation, dependency injection, and minimal boilerplate, FastAPI lets developers build, test, and iterate APIs much faster with fewer bugs.
FastAPI shines in microservices, real-time applications, ML/AI model serving, dashboards, event-driven APIs, and systems requiring WebSockets. Its async support makes it suitable where high concurrency is needed.
Integration with tools like Uvicorn, Starlette, Pydantic, automatic docs (Swagger UI/ReDoc), JSON Schema, good support for background tasks / WebSockets, plus ease of testing with e.g. pytest.
26,000+
companies worldwide using FastAPI in production
134M+
monthly downloads from PyPI
112
countries with FastAPI adoption
38%
of Python web developers use FastAPI (JetBrains 2025)
78,900+
GitHub stars, surpassing Flask
35%
enterprise adoption growth over past two years
38%
usage among Python web frameworks (up from 29% in 2024)
3.27M
daily downloads from PyPI
46%
of Python developers work on web development
1,200+
companies using FastAPI in India alone
Over a recent 6-month period, there were 137 FastAPI-skill vacancies in the UK alone, with year-on-year job ads showing substantial increases in demand.
Median annual salaries for FastAPI roles average £80,000 in the UK, with competitive packages ranging from €90k–€120k across Europe and similar premium rates in North America.
United States leads with ~5.1k companies, UK has ~1.4k companies, and India shows 1,000+ active job postings for FastAPI developers across major tech hubs.
FastAPI roles are highly remote-friendly, with many listings offering remote/hybrid options, enabling companies to source global talent and reduce hiring friction.
Uvicorn & Hypercorn dominate ASGI server deployments, Pydantic v2 achieves rapid adoption, with SQLAlchemy, Tortoise ORM, and Prisma as leading database solutions.
26,000+ companies across 112 countries use FastAPI in production. Over 90% of projects use Python type hints with automatic OpenAPI documentation generation.
Async endpoints used in >80% of new projects, Pydantic v2 migration accelerated, WebSocket support widely adopted for real-time applications.
pytest remains the leading choice with strong automated testing adoption in production FastAPI applications, ensuring reliability and maintainability.
As we advance into 2025, backend technologies are playing an even more decisive role in shaping digital businesses. FastAPI, a modern Python framework for building high-performance APIs, has become a preferred choice for companies aiming to deliver scalable, secure, and lightning-fast digital services. Businesses looking to hire FastAPI developers will find that securing skilled talent is no longer optional but a strategic imperative.
The statistics are compelling: FastAPI is no longer a niche Python framework — it's one of the most widely adopted backend solutions globally. As of 2025, over 26,000 companies across 112 countries use FastAPI in production, including tech leaders like Uber, Netflix, Microsoft, and Expedia. With 134+ million monthly downloads from PyPI, its adoption curve shows no signs of slowing down.
Much like the frontend world experienced with React, backend hiring is now seeing a crunch in FastAPI expertise. Job posting data from LinkedIn and Indeed shows 1,000+ active FastAPI job openings in India alone, with similar demand spikes in North America and Europe. In the UK, FastAPI salaries are averaging £80,000+, with year-on-year vacancy growth.
Connect with our client advisors today to access top FastAPI talent and transform your API development capabilities.
FastAPI is a modern, high-performance web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed for speed, simplicity, and developer productivity, making it one of the fastest-growing backend frameworks for creating scalable, type-safe, and production-ready APIs.
Built on Starlette and Pydantic, offering performance comparable to Node.js and Go with async/await support.
Generates interactive API docs (Swagger UI & ReDoc) automatically from type hints.
Powered by Pydantic for strict type validation, ensuring data integrity and reducing errors.
Native async/await support for handling thousands of concurrent connections efficiently.
High-Performance Python Framework
FastAPI was first released in 2018 by Sebastián Ramírez to solve the limitations of Flask while embracing Python's type hinting system. It quickly gained adoption in AI/ML projects and microservices, evolving into a mainstream framework used by companies like Netflix, Microsoft, and Uber.
Created by Sebastián Ramírez to solve Flask limitations while embracing Python's type hinting system.
Gained traction in AI/ML projects and microservices due to async support and automatic validation.
Major companies like Netflix, Microsoft, and Uber started using FastAPI in production systems.
Ranked among top 5 most loved frameworks in Stack Overflow Survey with exponential growth.
FastAPI stands out compared to other backend technologies with its modern approach, performance-focused features, and developer-friendly design.
Flask is simple and flexible but synchronous by default and requires extensions for data validation. FastAPI offers built-in validation, async support, and automatic docs, making it more production-ready.
Master these fundamental FastAPI concepts to build scalable, maintainable APIs that drive business success and digital transformation.
Clear, Pythonic syntax for defining endpoints and injecting reusable dependencies with minimal boilerplate.
Ensures clean, strongly-typed inputs and outputs with automatic validation and serialization.
Native async/await support enables handling thousands of concurrent requests efficiently.
Built-in support for Swagger UI and ReDoc, reducing development overhead and improving collaboration.
Natural fit with Python's AI ecosystem (TensorFlow, PyTorch) for model serving and deployment.
Built-in support for OAuth2, JWT tokens, and API key-based authentication out of the box.
FastAPI has rapidly become a preferred framework for modern API development, especially among companies seeking high-performance, scalable, and type-safe backend solutions.
Built on Starlette and Pydantic, offering performance comparable to Node.js and Go for high-concurrency applications.
Automatic documentation, type validation, and async support reduce development time and boilerplate code.
Pydantic ensures strict type validation while built-in security features provide robust authentication.
Perfect for AI/ML model serving with seamless integration into Python's data science ecosystem.
Excellent support for Docker, Kubernetes, and serverless architectures with optimized deployment.
Rapidly growing ecosystem with comprehensive documentation and active community support.
Skilled FastAPI developers bring comprehensive expertise in modern backend development, cloud technologies, and scalable architecture design.
Real-time dashboards, messaging, and IoT applications
Serving TensorFlow, PyTorch, and scikit-learn models
Distributed systems with event-driven design
AWS Lambda, Azure Functions, GCP Cloud Run
Automatic validation, interactive docs, and async features accelerate development from prototype to production.
Reduced boilerplate code, rapid development cycles, and easier maintenance lower total cost of ownership.
Handles everything from lightweight MVPs to enterprise-scale distributed systems with optimal performance.
Seamless integration with Python's AI ecosystem for model serving and data-driven applications.