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Python Llm Jobs in Texas (NOW HIRING)

Python AI Agent Developer - Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

Python Developer 3 to 4 Years (Framework Development & Agentic AI nice to have) We are building ... Collaborate with AI engineers to integrate Agentic AI systems (e.g., AI agents, LLM orchestration ...

Python Developer 3 to 4 Years (Framework Development & Agentic AI nice to have) We are building ... Collaborate with AI engineers to integrate Agentic AI systems (e.g., AI agents, LLM orchestration ...

Python developer - Dallas, Tx

Dallas, TX · On-site

$49.75 - $68.50/hr

LLM Integration: Develop integrations with LLM providers such as OpenAI, Gemini, Anthropic, and ... Create Python-based tools and connectors that enable agents to interact with APIs, databases ...

Python developer - Dallas, Tx

Dallas, TX · On-site

$49.75 - $68.50/hr

LLM Integration: Develop integrations with LLM providers such as OpenAI, Gemini, Anthropic, and ... Create Python-based tools and connectors that enable agents to interact with APIs, databases ...

Hiring: Python Full Stack Developer Dallas, TX (Onsite) W2 Only We are looking for a highly experienced Python Full Stack Developer with strong expertise in backend, cloud, and AI/LLM-based ...

Python Developer Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

The Python Developer will play a critical role in building and enhancing our Agentic AI platform ... LLM Integration: Integrate and optimize LLM-powered capabilities using platforms such as OpenAI ...

Python Developer Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

The Python Developer will play a critical role in building and enhancing our Agentic AI platform ... LLM Integration: Integrate and optimize LLM-powered capabilities using platforms such as OpenAI ...

Gen AI with Python

Dallas, TX · Hybrid

$49.75 - $68.50/hr

GenAI Engineer / GenAI Developer - Python Location: Dallas, TX (Hybrid) Employment Type: W2 Only ... Experience with LLM platforms such as OpenAI, AWS Bedrock, or Google Gemini. * Experience with ...

Python Engineer- USC/GC/ GC EAD/ H4 EAD- W2 Location: Charlotte NC/Plano TX - Look for local ... Integrate AI tools (including ChatGPT and other LLM-based solutions) into automation workflows for ...

Collaborate with AI engineers to integrate Agentic AI systems (e.g., AI agents, LLM orchestration ... Strong proficiency in Python (3.x) for ML and software development., with focus on OOP and modular ...

Python Developer with ML - Dallas, TX

Dallas, TX · On-site

$49.75 - $68.50/hr

Our team is looking for a skilled Python Developer for ML with deep expertise in framework design ... LLM orchestration frameworks like LangChain, LlamaIndex, Google ADK). • Ensure security ...

Data Scientist with Python Location: Dallas, TX below. Data Science Skills * Deploy and maintain ... Portfolio of LLM applications and sample projects * 2+ years of NLP experience using tools such as ...

Showing results 21-40

Python Llm information

What is a Python LLM?

A Python LLM job involves working with Large Language Models (LLMs) using Python to develop, fine-tune, and deploy AI models. Responsibilities may include data preprocessing, prompt engineering, model optimization, and integration with applications. Professionals in this role often work with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. They may also contribute to improving model efficiency, reducing bias, and ensuring ethical AI usage.

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

To excel as a Python LLM (Large Language Model) Engineer, you need strong skills in Python programming, machine learning, and natural language processing, typically supported by a degree in computer science or a related field. Proficiency with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and experience with model deployment platforms are often essential, alongside certifications in AI or data science. Effective communication, problem-solving abilities, and collaboration are important soft skills for working in interdisciplinary teams and delivering results in dynamic environments. These skills ensure the development, fine-tuning, and deployment of advanced language models that meet both technical and business objectives.

What are some common challenges faced by Python LLM engineers in their daily work?

Python LLM Engineers often encounter challenges related to optimizing model performance, managing large datasets, and adapting models to specific business needs. Working with large-scale language models requires balancing computational resource limitations with the need for high accuracy and efficiency. Collaboration with data scientists, product managers, and DevOps engineers is routine to ensure seamless model integration and deployment. Staying updated on the latest advancements in NLP and continuously improving models based on user feedback are also important aspects of the role.

What are the most commonly searched types of Python Llm jobs in Texas?

The most popular types of Python Llm jobs in Texas are:

What cities in Texas are hiring for Python Llm jobs?

Cities in Texas with the most Python Llm job openings:

Infographic showing various Python Llm job openings in Texas as of August 2026, with employment types broken down into 1% Internship, 88% Full Time, 6% Part Time, and 5% Contract. Highlights an 76% Physical, 7% Hybrid, and 17% Remote job distribution.

Python AI Agent Developer - Dallas, TX

Photon

Dallas, TX • On-site

$49.75 - $68.50/hr

Full-time

Re-posted 16 days ago


Job description


Python Developer 3 to 4 Years (Framework Development & Agentic AI nice to have)
We are building next-generation intelligent systems powered by AI and automation. Our team is looking for a skilled Python Developer with deep expertise in framework design and exposure to Agentic AI systems. You will play a pivotal role in architecting scalable frameworks, APIs, and integrations while enabling AI-driven agents to perform complex workflows securely and efficiently.
Key Responsibilities:
Design, develop, and maintain Python frameworks that provide reusable components and structure for applications.
Architect modular, scalable, and extensible frameworks for APIs, data processing, or AI integrations.
Implement best practices in software engineering: OOP, design patterns, modular architecture.
Develop APIs and SDKs for framework adoption across teams.
Collaborate with AI engineers to integrate Agentic AI systems (e.g., AI agents, LLM orchestration frameworks like LangChain, LlamaIndex, Google ADK).
Ensure security, reliability, and observability of framework components.
Write unit/integration tests and maintain CI/CD pipelines.
Document frameworks, APIs, and libraries for developer adoption.
Participate in code reviews, mentor junior developers, and contribute to technical design discussions.
Required Skills & Experience:
Strong proficiency in Python (3.x), with focus on OOP and modular design.
Proven experience in building frameworks, libraries, or SDKs (not just applications).
Expertise in design patterns, dependency injection, and plugin-based architectures.
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).
Proficiency in testing frameworks (PyTest, unittest) and CI/CD workflows.
Strong grasp of security practices (OAuth2, JWT, IAM integration).
Familiarity with cloud platforms (GCP, Azure, AWS) for deploying frameworks.
Nice to Have:
Experience with Agentic AI frameworks (LangChain, LlamaIndex, Google ADK, AutoGen).
Knowledge of LLM fine-tuning, prompt engineering, and guardrails.
Exposure to event-driven architectures (Kafka, Pub/Sub, Redis Streams).
Experience with observability tools (Prometheus, OpenTelemetry, Cloud Logging).
Contributions to open-source Python frameworks or libraries.
Ideal Candidate:
A framework builder mindset - you enjoy designing systems other developers will use.
Passionate about AI and automation, eager to experiment with agent-driven architectures.