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Fastapi Developer Jobs in Dallas, TX (NOW HIRING)

Full Stack Developer | React + FastAPI | 10+ Years Experience * 10+ years of full stack engineering experience across frontend and backend systems * Expert-level proficiency in React and Next.js ...

Senior AI Software Engineer

Plano, TX · On-site

$118K - $155K/yr

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry * Develop real-time data ... Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions * Collaborate with cross ...

Senior AI Software Engineer

Plano, TX · On-site

$118K - $155K/yr

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry * Develop real-time data ... Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions * Collaborate with cross ...

Python Developer

Frisco, TX · On-site

$47 - $65/hr

Experience with Python frameworks such as Django, Flask, or FastAPI * Good understanding of RESTful APIs and web services * Strong knowledge of object-oriented programming (OOP) * Experience with SQL ...

We are seeking a versatile Backend Lead to join our engineering team. In this role, you will be ... Expert-level Python 3.x skills, with experience in frameworks like FastAPI , Django , or Flask

Senior AI Software Engineer

Plano, TX · On-site

$118K - $155K/yr

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry * Develop real-time data ... Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions * Collaborate with cross ...

Senior AI Software Engineer

Plano, TX · On-site

$118K - $155K/yr

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry * Develop real-time data ... Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions * Collaborate with cross ...

... FastAPI/Flask, and cloud technologies. • Implement MLOps practices with MLflow/Kubeflow/SageMaker/Azure ML, CI/CD, and automated orchestration (Airflow, Prefect, Autosys). • Ensure data quality ...

Python AI Agent Developer - Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

Experience with FastAPI, Flask, Django or similar web frameworks. Solid understanding of APIs (REST, GraphQL) and API gateway integration. Knowledge of async programming (asyncio, aiohttp)

AI Engineer

Plano, TX · On-site

$42/hr

AI Engineer Work Location: Plano, TX Duration: Contract Note: Local Candidates Only, F2F is ... API development (preferably FastAPI in Python). * Ability to independently debug and triage ...

Role: GenAI Engineer Duration: Long Term Location: Plano, TX * Candidate must have 5+ years of ... API development (preferably FastAPI in Python). * Ability to independently debug and triage ...

Experience with FastAPI, Flask, Django or similar web frameworks. Solid understanding of APIs (REST, GraphQL) and API gateway integration. Knowledge of async programming (asyncio, aiohttp)

Senior AI Software Engineer

Plano, TX · On-site

$118K - $155K/yr

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry * Develop real-time data ... Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions * Collaborate with cross ...

Senior AI Software Engineer

Plano, TX · On-site

$118K - $155K/yr

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry * Develop real-time data ... Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions * Collaborate with cross ...

Senior AI Software Engineer

Plano, TX · On-site

$118K - $155K/yr

Build RESTful APIs using FastAPI and GraphQL APIs using Strawberry * Develop real-time data ... Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions * Collaborate with cross ...

We are seeking a versatile Backend Lead to join our engineering team. In this role, you will be ... Expert-level Python 3.x skills, with experience in frameworks like FastAPI , Django , or Flask

Showing results 41-60

Fastapi Developer information

See Dallas, TX salary details

$16

$52

$81

How much do fastapi developer jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for fastapi developer in Dallas, TX is $52.49, according to ZipRecruiter salary data. Most workers in this role earn between $40.10 and $64.23 per hour, depending on experience, location, and employer.

What is a FastAPI developer?

A FastAPI Developer is a software engineer who specializes in building web applications and APIs using the FastAPI framework, which is a modern, fast (high-performance) web framework for Python. FastAPI Developers are responsible for designing, developing, and maintaining backend services and APIs that are efficient, robust, and scalable. They often work with databases, authentication, and deployment processes, and ensure that the API endpoints adhere to best practices for security and performance. Their work is crucial for enabling smooth communication between front-end applications and backend systems.

What are the key skills and qualifications needed to thrive as a FastAPI developer?

To thrive as a FastAPI Developer, you need strong proficiency in Python programming, RESTful API design, and experience with FastAPI, often supported by a background in computer science or related fields. Familiarity with tools like SQL/NoSQL databases, Docker, and cloud platforms, as well as knowledge of asynchronous programming and API documentation tools like Swagger, is typically required. Excellent problem-solving skills, attention to detail, and effective communication set outstanding FastAPI developers apart. These skills are crucial for building reliable, high-performance APIs that meet modern application demands and facilitate seamless team collaboration.

What are some common challenges FastAPI developers face when integrating third-party services or APIs?

FastAPI Developers often encounter challenges when integrating third-party services, such as handling authentication protocols (like OAuth2), ensuring compatibility between JSON schemas, and managing asynchronous calls to avoid performance bottlenecks. It’s also common to troubleshoot and adapt to inconsistencies in external API documentation or rate limits. Collaborating closely with frontend teams and DevOps professionals helps streamline these integrations, ensuring robust, scalable API solutions.

What is the difference between Fastapi Developer vs Backend Developer?

AspectFastapi DeveloperBackend Developer
Required SkillsPython, Fastapi, REST APIs, async programmingMultiple languages (Python, Java, Node.js), REST/SOAP APIs, databases
Work EnvironmentWeb development, API-focused projects, microservicesBroader software development, server-side logic, database management
Industry UsageTech startups, SaaS, API-driven servicesEnterprise, e-commerce, finance, various industries

Fastapi Developers specialize in building high-performance APIs using Python and Fastapi, often within microservices architectures. Backend Developers have a broader scope, working with multiple languages and technologies to develop server-side applications across various industries. While Fastapi Developers focus on API efficiency, Backend Developers handle comprehensive backend systems.

What are the most commonly searched types of Fastapi Developer jobs in Dallas, TX?

The most popular types of Fastapi Developer jobs in Dallas, TX are:

What job categories do people searching Fastapi Developer jobs in Dallas, TX look for?

The top searched job categories for Fastapi Developer jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Fastapi Developer jobs?

Cities near Dallas, TX with the most Fastapi Developer job openings:

Infographic showing various Fastapi Developer job openings in Dallas, TX as of August 2026, with employment types broken down into 82% Full Time, 4% Part Time, and 14% Contract. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $109,184 per year, or $52.5 per hour.

AgenticAI Workflow Engineer | Onsite

Photon

Dallas, TX • On-site

Full-time

Posted 15 days ago


Job description


Agentic AI Workflow Engineer
We are seeking an Agentic AI Workflow Engineer to design, build, and optimize intelligent AI-driven workflows using Large Language Models (LLMs), AI agents, and enterprise automation frameworks. You will develop agentic applications that can reason, retrieve knowledge, interact with enterprise systems, and automate complex business processes.
The ideal candidate combines strong software engineering fundamentals with hands-on experience in Generative AI application development, agent orchestration, RAG pipelines, prompt engineering, and API integrations.
Technical Stack:
LLMs:
OpenAI GPT, Claude, Gemini, Llama, Mistral, and other open-source LLMs.
Agent Frameworks:
LangGraph, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen.
Agentic AI Concepts:
Multi-Agent Systems (MAS), Agent Planning, Tool Calling, Memory Management, Human-in-the-Loop (HITL) workflows.
Development:
Python, FastAPI, REST APIs, Async Programming.
RAG & Knowledge Engineering:
Vector Databases, PostgreSQL, pgvector, Redis Vector Search, Elasticsearch, Embeddings, Semantic Search, Retrieval Optimization.
Workflow Orchestration:
LangGraph workflows, Agent State Management, Workflow Automation, Event-driven workflows.
Cloud & Deployment:
AWS/Azure/GCP, Docker, CI/CD pipelines, API deployment.
Tools:
Prompt Engineering, AI Workflow Design, LLM Evaluation, Agent Monitoring, GenAI Optimization.
Key Responsibilities:
  • Develop and orchestrate AI agent workflows using LangGraph, LangChain, and multi-agent architectures.

  • Design agent behaviors including:

  • Goals and instructions

  • Tool usage

  • Reasoning flows

  • Memory management

  • Error handling and recovery

  • Build RAG-based AI applications by integrating enterprise knowledge sources, vector databases, and embedding models.

  • Develop AI agents capable of interacting with enterprise systems through APIs, databases, and external tools.

  • Implement function calling and tool integrations enabling agents to perform real-world actions.

  • Create reusable agent components, workflow templates, and AI automation patterns.

  • Develop backend services and APIs using Python, FastAPI, and asynchronous programming.

  • Optimize prompts, agent workflows, and retrieval strategies to improve:

  • Accuracy

  • Response quality

  • Latency

  • Cost efficiency

  • Implement Human-in-the-Loop workflows for approval-based enterprise processes.

  • Build evaluation pipelines to measure agent performance, hallucination rates, and task completion accuracy.

  • Deploy and monitor GenAI applications using cloud platforms, containerization, and observability tools.

  • Collaborate with AI architects, product managers, and domain teams to convert business processes into agentic AI solutions.

Required Qualifications:
  • 3-6 years of experience in software engineering, AI engineering, or Generative AI application development.

  • Hands-on experience building LLM-powered applications using Python.

  • Strong understanding of:

  • LLM concepts

  • Prompt engineering

  • RAG architecture

  • AI agent workflows

  • Vector search concepts

  • Experience with agent frameworks such as:

  • LangGraph

  • LangChain

  • LlamaIndex

  • Semantic Kernel

  • CrewAI

  • Experience integrating LLM applications with REST APIs, databases, and enterprise systems.

  • Knowledge of vector databases, embeddings, semantic search, and retrieval optimization techniques.

  • Experience developing production-quality Python applications using FastAPI or similar frameworks.

  • Familiarity with Docker, cloud deployment, CI/CD practices, and API security.

  • Understanding of AI evaluation techniques including:

  • Response quality assessment

  • Prompt testing

  • Agent workflow validation

  • Exposure to AI governance concepts:

  • Responsible AI

  • Guardrails

  • Data privacy

  • Prompt injection prevention

Preferred Qualifications:
  • Experience building autonomous AI agents or multi-agent workflows.

  • Experience with enterprise automation, IT operations, customer service, or business process automation use cases.

  • Experience with observability platforms for monitoring AI applications.

  • Contributions to open-source AI frameworks or GenAI projects.