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Python Fastapi Developer Jobs in Union City, CA (NOW HIRING)

Sadient

Data Engineer (Senior)

San Francisco, CA · On-site

$124K - $169K/yr

The backend is built using Python (FastAPI) and supported by AWS services such as Lambda and ... Redis Bonus Skills Experience in financial technology Full-stack engineering capabilities with ...

FlexAI

Senior Full Stack Engineer

Santa Clara, CA · On-site

... developer tools, marketplace, billing, admin) • Develop high-performance UIs using React • Design and implement APIs and backend services using Python (FastAPI) and/or Node.js • Define clean ...

AI Talent Now

Senior Product Engineer

Palo Alto, CA · On-site

$140K - $250K/yr

Experience with Python, FastAPI, and a background in B2B SaaS preferred * Top 15 school required if under 2 years of experience Company Context * Transitioning all engineers to full-stack roles

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How much do python fastapi developer jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for python fastapi developer in Union City, CA is $66.77, according to ZipRecruiter salary data. Most workers in this role earn between $55.05 and $75.87 per hour, depending on experience, location, and employer.

What is a Python FastAPI developer?

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 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 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 cities near Union City, CA are hiring for Python Fastapi Developer jobs?

Cities near Union City, CA with the most Python Fastapi Developer job openings:

Python Fastapi Developer jobs near you

GenAI Engineer - LLM Infrastructure & Inference Services

San Jose, CA

2T Consulting
IT Services • 51 - 200 employees
Learn more about 2T Consultingexternal

$126K - $165K/yr

Full-time

Posted 13 days ago

Job description

We are looking for a GenAI Engineer with strong expertise in LLM infrastructure, model deployment, and high-performance inference services. The ideal candidate will build and manage scalable enterprise GenAI platforms across GPU infrastructure and cloud environments.

Key Responsibilities
  • Deploy, host, and manage Large Language Models (LLMs) on GPU infrastructure for production environments.
  • Build scalable, high-performance inference services using vLLM, TensorRT-LLM, Triton Inference Server, and Ray Serve.
  • Optimize model serving for latency, throughput, GPU utilization, and cost efficiency.
  • Develop AI platform services and APIs using Python, FastAPI, Microservices, and Kubernetes.
  • Implement RAG pipelines, vector databases, and agentic AI frameworks such as LangChain and LangGraph.
  • Manage GPU infrastructure, containerization, and cloud deployments across AWS, Azure, or GCP.
  • Establish MLOps/LLMOps practices including CI/CD, model deployment, monitoring, observability, and governance.
  • Perform performance tuning, benchmarking, capacity planning, and production support for enterprise GenAI platforms.
  • Collaborate with architects, data scientists, and product teams to deliver scalable, secure, and reliable AI solutions.
Core Technologies
  • LLM: vLLM, TensorRT-LLM, Triton Inference Server, Ray Serve
  • AI/GenAI: RAG, LangChain, LangGraph, Vector Databases
  • Development: Python, FastAPI, Microservices
  • Infrastructure: Kubernetes, Docker, GPU Infrastructure
  • Cloud: AWS, Azure, GCP
  • MLOps/LLMOps: CI/CD, Monitoring, Observability, Model Deployment, Governance

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