Hire Nearshore FastAPI Developer

FastAPI helps you build APIs that are fast, reliable, and easier to maintain. Its async support and type validation let you handle high-load requests and reduce bugs before they hit production. That matters when your product needs to scale quickly or respond to user demands in real time.

Scaling a FastAPI project requires consistent developer availability and quick iteration. That can be hard when local talent is limited or costly. Nearshore developers in Latin America work in overlapping time zones and typically charge $30-80 per hour, so you can debug, deploy, and iterate during your business day without long delays.

Why Hire a Nearshore FastAPI Developer?

Hiring nearshore FastAPI developers gives you access to skilled Python engineers who work in overlapping time zones, making real-time collaboration and rapid iteration possible. You can scale your team efficiently, maintain technical quality, and avoid the delays and competition often encountered with local hires.

Cost-effective Solutions

Nearshore rates in Latin America range from $30 to $80 per hour, depending on country, skill level, and project complexity. Mid-level FastAPI developers typically fall into the $40-60 per hour range, while senior developers with 5+ years of Python experience command $50-80 per hour. Compare this to US-based developers at $110-160 per hour, and companies achieve 40-65% cost savings while maintaining technical quality.

These savings scale linearly with team size. A three-person backend team costs $25-40K per month nearshore versus $55-80K domestically. Over a six-month project, that difference exceeds $180K in direct labor costs.

Time Zone Compatibility

Latin American developers work during hours that overlap substantially with US time zones. A developer in Mexico City or Bogotá starts their day at 9 AM local time, which corresponds to 11 AM Eastern or 8 AM Pacific. This 6-8 hour overlap enables:

• Real-time standup meetings without requiring anyone to work unusual hours

• Same-day code reviews and pull request feedback

• Live debugging sessions when production issues occur

• Synchronous collaboration during sprint planning and retrospectives

The alternative is offshore development in Asia, where a 12-hour time difference forces asynchronous workflows. Questions asked in the morning get answered the next day. Production issues were discovered at 2 PM wait until the next morning for developer attention. This delay compounds over weeks and months.

Skilled Talent Pool

Latin America has a growing pool of Python developers experienced in modern frameworks and cloud platforms. They work with the same tech stacks as their US counterparts, deploy to AWS and Google Cloud, use Docker and Kubernetes, write tests with pytest, and follow agile methodologies. 

Geographic distance doesn’t create a capability gap, and many developers are ready to collaborate in overlapping business hours.

What is FastAPI?

FastAPI is a modern Python framework designed for building APIs and async backends. It runs on ASGI (Asynchronous Server Gateway Interface), allowing it to handle many concurrent requests without blocking threads during database queries or external API calls.

The framework leverages Python’s type hints and Pydantic for automatic data validation and serialization, reducing boilerplate and runtime errors while keeping code maintainable. FastAPI also generates API documentation automatically via OpenAPI and Swagger UI, so you don’t need separate tools to document endpoints.

This combination of async support, automatic validation, and built-in documentation makes FastAPI practical for APIs, microservices, and backend services where performance, clarity, and maintainability are critical. 

FastAPI vs Other Python Frameworks

FastAPI typically delivers higher throughput and lower latency than Flask or Django in API workloads because it uses async/await and ASGI, while Flask and Django rely more on synchronous request handling.

Feature	FastAPI	Flask	Django
Performance	High throughput for I/O‑bound APIs	Moderate, synchronous	Moderate, synchronous by default
Async Support	Native ASGI (built‑in)	Requires extensions	Partial; ecosystem still largely sync
Type Validation	Built‑in via Pydantic	Manual or via libraries	Through DRF/forms
API Documentation	Auto‑generated (OpenAPI/Swagger)	Requires extensions	Requires DRF + extensions
Learning Curve	Moderate (due to async/type hints)	Low	Higher (batteries‑included)
Best Use Case	API‑first, microservices	Simple apps/APIs	Full‑stack applications

Benefits of Using FastAPI

FastAPI combines three technical capabilities that made it popular:

Asynchronous by default. The framework uses Python's async/await syntax throughout, allowing I/O operations to run concurrently without blocking execution threads. This matters for applications that make multiple database queries, call external APIs, or process file uploads within a single request.

Automatic data validation. FastAPI uses Pydantic models to validate request data at runtime. Define a data model with type hints, and FastAPI automatically validates incoming JSON against that schema, returning detailed error messages when validation fails. This eliminates boilerplate validation code and catches type errors before they reach your business logic.

Interactive documentation. Every FastAPI application includes automatically generated Swagger UI and ReDoc interfaces. Developers can test endpoints directly from the browser, see request/response schemas, and explore available endpoints without writing documentation separately.

Roles and Responsibilities of a FastAPI Developer

FastAPI developers focus on backend systems, specifically APIs that serve data to frontend applications, mobile apps, or other services. Their work centers on designing endpoints, processing requests, and integrating with databases and external services.

Typical Day-to-Day Tasks

A FastAPI developer usually:

• Writes API endpoints to handle HTTP requests and return JSON responses.

• Designs Pydantic models to define request/response schemas and validate data automatically.

• Implements authentication and authorization using JWT tokens or OAuth2 flows.

• Integrates with databases through ORMs like SQLAlchemy or async libraries like Tortoise ORM.

• Writes unit tests with pytest and integration tests to ensure endpoints and database operations work correctly.

• Optimizes query performance with indexing, caching, and lazy loading strategies.

• Deploys applications to cloud platforms using Docker and orchestration tools like Kubernetes.

• Monitors performance and troubleshoots issues in staging and production environments.

This requires solid knowledge of Python and understanding the broader architecture of web applications. Developers need to know when to use background tasks, how to structure projects for maintainable code, and which middleware to apply for logging, error handling, and request processing.

Project Types Using FastAPI

FastAPI appears most frequently in these application types:

SaaS platforms that provide APIs for customer applications. The framework's automatic documentation and type validation reduce the support burden when third parties integrate with your API.

Data processing pipelines that accept data from various sources, transform it, and store it in databases or data warehouses. FastAPI's async capabilities handle high throughput without blocking on I/O operations.

AI/ML integrations where frontend applications need to call machine learning models for predictions, classifications, or recommendations. FastAPI serves model inference endpoints efficiently, handling concurrent requests without resource bottlenecks.

Microservices architectures where multiple small services communicate via HTTP APIs. FastAPI's performance characteristics and lightweight nature make it suitable for building distributed systems where services need to handle high request volumes.

Real-time applications using WebSockets for bidirectional communication. FastAPI's ASGI foundation supports WebSocket connections natively, enabling real-time features like chat systems, live dashboards, or collaborative editing tools.

FastAPI Developer Experience Levels

FastAPI developers range from juniors building simple APIs with guidance to seniors and experts designing systems, optimizing performance, and guiding architectural decisions. Mid-level developers handle independent features, database design, and testing, taking on more responsibility as experience increases.

Seniority Levels: Junior to Expert

Junior developers (0-2 years) understand Python basics and can build simple CRUD APIs with guidance. They write endpoints, define Pydantic models, and perform basic database operations. They need direction on architecture decisions and code organization. Typical hourly rates fall between $30-45.

Mid-level developers (3-5 years) work independently on feature development. They design database schemas, implement authentication systems, write comprehensive tests, and make architectural recommendations within established patterns. They understand when to use background tasks, how to structure projects with multiple modules, and how to optimize database queries. Rates typically range from $45-65 per hour.

Senior developers (5+ years) lead technical decisions, design system architectures, and mentor junior team members. They have experience scaling applications, optimizing performance under load, implementing caching strategies, and debugging complex production issues. They understand trade-offs between different architectural approaches and can evaluate whether FastAPI fits a given use case. Senior rates range from $65-80 per hour.

Expert developers (8+ years) have built multiple production systems with FastAPI or similar frameworks. They contribute to open-source projects, write technical documentation, and solve architectural problems that require deep framework knowledge. They might implement custom middleware, extend the framework for specific use cases, or architect multi-region deployments. Expert rates can exceed $80 per hour.

Technical Evaluation Process

Evaluation should test actual job responsibilities rather than algorithm puzzles. Effective technical assessments include:

Take-home projects where candidates build a small API with specific requirements. The project should include authentication, database operations, input validation, and error handling. Review the submitted code for organization, testing coverage, error handling patterns, and whether they followed FastAPI best practices.

Code review sessions where candidates explain their architectural decisions, discuss trade-offs they considered, and walk through how they would extend the application. This reveals whether they understand why they made certain choices or simply copied patterns without comprehension.

System design discussions for senior roles, covering how they would architect a specific application. Ask about database schema design, caching strategies, authentication approaches, and how they would handle scaling challenges. Strong candidates discuss trade-offs and ask clarifying questions rather than jumping to a single solution.

Live coding exercises focused on debugging existing code or adding a feature to an existing codebase. This tests whether candidates can read unfamiliar code, identify issues, and make changes without breaking existing functionality.

Soft Skills and Communication Checks

Remote collaboration requires clear communication, proactive problem-solving, and reliable work habits. Assessment should verify:

English proficiency through conversation during interviews. The developer needs to explain technical concepts, describe their approach to problems, and ask clarifying questions about requirements. Written communication matters equally for code reviews, pull request descriptions, and async updates.

Remote work experience and their approach to staying connected with distributed teams. Ask about their typical workday structure, how they communicate blockers, and how they handle working across time zones.

Problem-solving approach when facing unclear requirements or technical obstacles. Strong candidates ask questions to clarify ambiguity, research solutions before escalating, and communicate their progress and blockers clearly.

Initiative and ownership demonstrated through examples of improvements they suggested, technical debt they identified, or processes they helped implement. Remote teams need self-directed developers who identify problems proactively rather than waiting for explicit instructions.

Nearshore Hiring Process

A well-planned process helps bring developers on board efficiently while maintaining quality. It usually follows a few key stages:

Step-by-Step Hiring Flow

1. Requirements gathering (1-2 days): Define the technical skills needed, project context, team structure, and budget constraints. Specify whether you need full-stack capabilities, specific framework versions, or experience with particular cloud platforms.

   
   

2. Candidate sourcing (2-3 days): Pre-vetted candidates from talent pools get matched against requirements. This step moves faster when working with partners who maintain active developer networks.

   
   

3. Initial screening (2-3 days): Candidates complete technical assessments and initial interviews to verify baseline competency and communication skills.

   
   

4. Technical interviews (3-5 days): Deep technical evaluations including code reviews, system design discussions, and live problem-solving sessions with your technical team.

   
   

5. Final interviews (1-2 days): Cultural fit assessment and discussion of working arrangements, expectations, and project details.

   
   

6. Offer and onboarding (2-3 days): Contract negotiation, equipment setup, repository access, and initial task assignment.

   
   

Estimated Time to Hire

Using pre-vetted candidates can cut hiring time considerably. For most roles, it takes about 5–10 business days from defining requirements to the developer’s start date. More specialized or senior positions may take 15–20 business days.

This timeline assumes timely feedback and interview scheduling - any delays on your side will naturally extend it.

How Much Does It Cost to Hire a FastAPI Developer?

Nearshore FastAPI developer costs depend on experience level, specific technical skills, and engagement model. 

Hourly and Monthly Rate Ranges

Latin America nearshore rates range from $30 to $80 per hour for Python developers with FastAPI experience. Monthly costs for full-time developers (160 hours) fall between $6,000 and $13,000 depending on seniority.

These rates typically include the developer's salary, benefits, equipment, and infrastructure costs when working through staffing partners. Direct hiring requires adding 30-40% to base salary for benefits, payroll taxes, and compliance costs.

Price by Developer Level: Junior, Mid, Senior

Level	Hourly	Monthly (160 hrs)	Key Responsibilities
Junior (0-2 yrs)	$30-40	$4.8k-6.4k	Basic CRUD, simple endpoints, guided work
Mid (3-5 yrs)	$40-60	$6.4k-9.6k	Independent features, DB design, testing
Senior (5+ yrs)	$50-80	$8k-12.8k	Architecture, performance, mentoring
Expert (8+ yrs)	$80+	$12.8k+	System design, scaling, technical leadership

Projects often combine multiple experience levels. For example, a team with one senior developer, two mid-level developers, and one junior balances cost and capability while keeping code quality under senior oversight.

Get Started Today

Finding the right FastAPI developer works best when requirements are clear and the evaluation process is efficient. Pre-vetted candidates help shorten hiring time without compromising quality.

Share your project details, tech stack, and timeline. Candidates that match your criteria are usually ready for review within 24–48 hours, with resumes showing experience, past projects, and sample code when available.

Brief discovery calls help clarify project scope, team needs, and technical requirements. They ensure the developer’s experience aligns with the work and set realistic expectations for onboarding.

You can also connect with our team to review available FastAPI developer profiles and discuss which experience level fits your project needs.

Frequently Asked Questions

How fast can I hire a FastAPI developer?

With pre‑screened candidates, you can typically have a developer ready in about 5–10 business days after discussing your requirements. That timeline covers interviews, technical checks, and basic onboarding. Specialized roles or very senior hires may take closer to 15–20 business days to match the right experience.

What makes nearshore better than offshore?

Nearshore teams in Latin America work in time zones that overlap with US business hours, which supports real‑time collaboration, same‑day feedback, and meetings without unusual schedules. Communication styles and English proficiency tend to align well with North American teams, helping reduce coordination overhead that offshore teams often face with large time differences.

Do Leanware developers work in my time zone?

Yes. Leanware’s developers are based in Colombia and work hours that significantly overlap with US time zones, enabling participation in standups, planning sessions, and real‑time debugging during your core business hours.

What kinds of FastAPI projects have these developers completed?

FastAPI developers working through nearshore providers have delivered a range of backend services, including microservices for SaaS platforms, APIs for data‑intensive systems, real‑time endpoints with WebSockets, and machine learning inference services. Common technology combinations include FastAPI with PostgreSQL, Redis for caching, containerization with Docker, and cloud deployments on platforms like AWS and Google Cloud.

Do FastAPI developers have cloud deployment experience?

Yes. Most developers with mid‑ to senior‑level experience have deployed applications on cloud platforms such as AWS, Google Cloud, and Azure. They handle containerization, serverless functions, CI/CD pipelines, monitoring, and basic infrastructure tasks that make deployment and scaling smoother.

What FastAPI‑specific skills are evaluated?

Evaluations focus on key capabilities such as async/await patterns, dependency injection, Pydantic model design, automatic API documentation, middleware for authentication and logging, database integration, and background task handling. Reviews check that code follows FastAPI conventions and remains clear and testable.

What happens if a developer’s performance isn’t a good fit?

Replacement policies vary by engagement, but many nearshore models include trial periods during which substitutions can be made quickly if expectations aren’t met. Typically, a replacement can be identified and onboarded within a few business days if issues can’t be resolved through feedback and support.

What testing practices do FastAPI developers use?

Experienced FastAPI developers use pytest for unit and integration tests, pytest‑cov for coverage measurement, and integrate tests into CI/CD workflows. They mock external systems for isolation, and senior engineers often write tests before implementation where appropriate.

What performance optimization experience do FastAPI developers have?

Developers often employ caching strategies (e.g., Redis), database query tuning, async I/O patterns to avoid blocking, connection pooling, and response compression. They use profiling tools such as py‑spy or cProfile to find bottlenecks and adjust implementations accordingly.