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Python Fastapi Developer Jobs in Lake Mary, FL (NOW HIRING)

Kavaliro

Full Stack Engineer

Orlando, FL · On-site

Collaborate with DevOps to deploy and monitor applications in cloud or on-prem environments ... Strong proficiency in Java (Spring Boot or similar) , Python (Flask, Django, or FastAPI) , and C/C ...

Kavaliro

Full Stack Engineer

Orlando, FL · On-site

Collaborate with DevOps to deploy and monitor applications in cloud or on-prem environments ... Strong proficiency in Java (Spring Boot or similar) , Python (Flask, Django, or FastAPI) , and C/C ...

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$51

$75

How much do python fastapi developer jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for python fastapi developer in Lake Mary, FL is $51.26, according to ZipRecruiter salary data. Most workers in this role earn between $42.26 and $58.22 per hour, depending on experience, location, and employer.

What is a Python FastAPI Developer job?

A Python FastAPI Developer is responsible for designing, developing, and maintaining backend applications using FastAPI, a modern web framework for building APIs with Python. They work on creating high-performance APIs, integrating with databases, implementing authentication, and ensuring scalability. This role often involves working with asynchronous programming, cloud services, and containerization tools like Docker. Developers collaborate with teams to create efficient, secure, and well-documented API endpoints for web and mobile applications.

What are the key skills and qualifications needed to thrive in the Python Fastapi Developer position, and why are they important?

To thrive as a Python FastAPI Developer, you need strong proficiency in Python programming, experience designing RESTful APIs with FastAPI, and a background in web development concepts. Familiarity with version control systems like Git, containerization tools such as Docker, and knowledge of cloud platforms or SQL/NoSQL databases are commonly required, and certifications in cloud services or Python development can be advantageous. Excellent problem-solving skills, effective communication, and the ability to collaborate in agile teams help developers contribute efficiently to complex projects. These competencies ensure robust, scalable backend solutions and smooth coordination within development teams to meet business goals.

What are some typical daily tasks for a Python FastAPI Developer?

A Python FastAPI Developer typically spends their day designing, developing, and maintaining RESTful APIs to support web or mobile applications. This involves writing clean and efficient Python code, collaborating with frontend developers or other backend engineers to integrate new features, and ensuring the application meets performance and security standards. Developers also participate in code reviews, debugging, and continuous integration processes, while regularly communicating with product managers or stakeholders to align on project requirements. Staying up to date with FastAPI enhancements and industry best practices is also a common part of the role.

What cities near Lake Mary, FL are hiring for Python Fastapi Developer jobs? Cities near Lake Mary, FL with the most Python Fastapi Developer job openings:
Python Fastapi Developer jobs near you
Backend Python Developer - AI/ML

Backend Python Developer - AI/ML

Snowrelic Inc

Orlando, FL • On-site

Full-time

Posted 26 days ago

Job description

Job : Backend Python Developer – AI/ML

Location : Orlando preferable, Las Vegas

Skills : Python backend developer, FastAPI, RESTful APIs, Azure, LLM APIs, AI agent frameworks, LangChain, AutoGen, Semantic Kernel, cloud services, vector databases, RAG workflows

job Description : 

Role: Backend Python Developer – AI/ML

Orlando preferable, Las Vegas possible (Onsite)

Required Skills & Experience:

  • 5+ years of experience as a Python backend developer
  • Solid hands-on experience with FastAPI, Flask, or Django REST frameworks
  • Strong knowledge of RESTful APIs, microservices, and asynchronous programming
  • Hands n Experience with Azure 
  • Experience integrating LLM APIs (OpenAI, HuggingFace Inference API, etc.) into real-world applications
  • Experience with AI agent frameworks such as LangChain, AutoGen, or Semantic Kernel
  • Proven ability to deploy containerized apps using Docker, including LLM inference services and agent-based tools
  • Familiarity with vector databases and RAG workflows
  • Exposure to cloud services (AWS, GCP, Azure) and CI/CD pipelines