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Fastapi Jobs in California (NOW HIRING)

2T Consulting

$121K - $159K/yr

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.

2T Consulting

$104K - $137K/yr

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.

2T Consulting

$130K - $170K/yr

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.

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See California salary details

$117K

$132.2K

$149.3K

How much do fastapi jobs pay per year?

As of Sep 9, 2026, the average yearly pay for fastapi in California is $132,195.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,341.00 and $137,092.00 per year, depending on experience, location, and employer.

What is a FastAPI?

A FastAPI job typically involves developing, maintaining, and optimizing web applications and APIs using the FastAPI framework. FastAPI is a modern, high-performance web framework for Python that is designed for building APIs quickly with automatic OpenAPI generation. Professionals in this role are expected to have experience with Python, asynchronous programming, and API development, often working with databases, authentication, and cloud services.

What are the typical daily responsibilities of a FastAPI developer?

As a FastAPI Developer, your daily tasks typically include designing and implementing RESTful APIs, writing efficient and maintainable code, and performing thorough testing to ensure reliability and performance. You may also collaborate closely with frontend developers, DevOps engineers, and QA teams to integrate new features and troubleshoot issues. Regular code reviews, documentation, and participation in agile development meetings are common parts of the workday. This collaborative and dynamic environment allows you to make a direct impact on the product while growing your skills through hands-on problem-solving and teamwork.

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

To thrive as a FastAPI Developer, you need strong proficiency in Python, REST API design, and knowledge of web frameworks, ideally supported by a relevant degree or industry certifications. Familiarity with tools like Docker, Git, asynchronous programming, and testing frameworks such as Pytest is often required. Excellent problem-solving skills, adaptability, and clear communication are valuable soft skills in this role. These competencies ensure robust API development, seamless collaboration, and the delivery of high-quality software solutions in agile environments.

What are the most commonly searched types of Fastapi jobs in California?

The most popular types of Fastapi jobs in California are:

What are popular job titles related to Fastapi jobs in California?

For Fastapi jobs in California, the most frequently searched job titles are:

What job categories do people searching Fastapi jobs in California look for?

The top searched job categories for Fastapi jobs in California are:

What cities in California are hiring for Fastapi jobs?

Cities in California with the most Fastapi job openings:

Fastapi jobs near you
Infographic showing various Fastapi job openings in California as of September 2026, with employment types broken down into 72% Full Time, 21% Part Time, and 7% Contract. Highlights an 76% Physical, 5% Hybrid, and 19% Remote job distribution, with an average salary of $132,195 per year, or $63.6 per hour.

GenAI Engineer - LLM Infrastructure & Inference Services

Atherton, CA • On-site

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

$130K - $170K/yr

Full-time

Posted 12 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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