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Fastapi Programmer Jobs in Florida (NOW HIRING)

Full Stack Developer (Python + React + Azure) Location: Miami, FL (Onsite) Experience 10+ Years ... Design and build scalable backend services using Python (FastAPI, Flask, Django) and .NET (C#) for ...

AI/ML Engineer

Sunrise, FL · On-site

$50 - $54/hr

Looking for candidates who can build APIs around AI/ML solutions using Flask or FastAPI. * Database ... engineering, model evaluation, REST API development (Flask, FastAPI), database management (SQL ...

DevOps Engineer

Sarasota, FL · On-site

$50.75 - $69.75/hr

Experience working with Python web frameworks (FastAPI, Flask, etc.) DevOps & CI/CD * Experience with Agile workflows (Jira, sprints) * Hands-on experience creating and maintaining CI/CD pipelines ...

AI LEAD L1

Tampa, FL · On-site

$60K - $135K/yr

The ideal candidate will have strong expertise in Python programming, FastAPI, and cloud platforms (AWS, Azure, or GCP). This role requires a deep understanding of system architecture design ...

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Fastapi Programmer information

What cities in Florida are hiring for Fastapi Programmer jobs? Cities in Florida with the most Fastapi Programmer job openings:
Backend Python Developer - AI/ML

Backend Python Developer - AI/ML

Snowrelic Inc

Orlando, FL • On-site

Full-time

Re-posted 16 days ago


Job description

Job : Backend Python Developer – AI/ML

Location : Orlando preferable, Las Vegas

Skills : Python backend developer, FastAPI, RESTful APIsAzure, 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