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Python Llm Jobs in Plano, TX (NOW HIRING)

Photon

Agentic AI Workflow Engineer

Dallas, TX · On-site

Hands-on experience building LLM-powered applications using Python. * Strong understanding of: * LLM concepts * Prompt engineering * RAG architecture * AI agent workflows * Vector search concepts

Infosys

Gen AI Python Engineer

Plano, TX · On-site

... LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth ... Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while ...

Infovision

AI Engineer

Dallas, TX · On-site

AI Engineer | Python + GenAI + Data | 8+ Years Experience 8+ years of engineering experience with ... for LLM applications Experience building and optimizing RAG (Retrieval-Augmented Generation ...

InfoVision, Inc.

AI Engineer

Dallas, TX · On-site

AI Engineer | Python + GenAI + Data | 8+ Years Experience * 8+ years of engineering experience with ... Proficient with LLM APIs - OpenAI, Anthropic, Gemini, and open-source models (LLaMA, Mistral ...

BC Forward

Java + Python AI Agent Engineer

Addison, TX · On-site

$68.25/hr

Java + Python AI Agent Engineer Location: Addison, TX Duration: Contract - 7 months (potential ... Familiarity with LLM-based agents and prompt engineering. Work Arrangement and Interview Process ...

New

Precision Technologies Corp

AI Engineer

Dallas, TX · On-site

Contract Key Skills - AI, Python, Rag, LLM Overview We are seeking an AI Engineer with proven experience in building and scaling AI-powered applications . This role combines hands-on development with ...

TXU Energy

Lead Developer - Python , Gen AI

Irving, TX · Hybrid

$134K - $165K/yr

Operating as a hands-on individual contributor, you will own the design and implementation of a diverse array of Python-based services which integrate LLM capabilities directly into our ecosystem ...

Vst

Lead Developer - Python , Gen AI

Irving, TX · Hybrid

$134K - $165K/yr

Operating as a hands-on individual contributor, you will own the design and implementation of a diverse array of Python-based services which integrate LLM capabilities directly into our ecosystem ...

Vistra Corp.

Lead Developer - Python , Gen AI

Irving, TX · On-site

$134K - $165K/yr

Operating as a hands-on individual contributor, you will own the design and implementation of a diverse array of Python-based services which integrate LLM capabilities directly into our ecosystem ...

Vistra Energy

Lead Developer - Python , Gen AI

Irving, TX · Hybrid

$134K - $165K/yr

Operating as a hands-on individual contributor, you will own the design and implementation of a diverse array of Python-based services which integrate LLM capabilities directly into our ecosystem ...

Photon

Backend Lead - Python - Dallas, TX

Dallas, TX · On-site

The ideal candidate is a Python expert who thrives on complex system design, concurrency, and the ... Experience with LLM fine-tuning or local model deployment (vLLM, Ollama). * Knowledge of ...

Luminant

Lead Developer - Python , Gen AI

Irving, TX · Hybrid

$134K - $165K/yr

Operating as a hands-on individual contributor, you will own the design and implementation of a diverse array of Python-based services which integrate LLM capabilities directly into our ecosystem ...

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All JobsPython Llm JobsPython Llm Jobs in Plano, TX

Python Llm information

See Plano, TX salary details

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$56

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How much do python llm jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for python llm in Plano, TX is $56.11, according to ZipRecruiter salary data. Most workers in this role earn between $46.25 and $63.75 per hour, depending on experience, location, and employer.

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 popular job titles related to Python Llm jobs in Plano, TX? For Python Llm jobs in Plano, TX, the most frequently searched job titles are:
What job categories do people searching Python Llm jobs in Plano, TX look for? The top searched job categories for Python Llm jobs in Plano, TX are:
What cities near Plano, TX are hiring for Python Llm jobs? Cities near Plano, TX with the most Python Llm job openings:
Python Llm jobs near you
Infographic showing various Python Llm job openings in Plano, TX as of August 2026, with employment types broken down into 2% Internship, 89% Full Time, 3% Part Time, and 6% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $116,700 per year, or $56.1 per hour.

Agentic AI Workflow Engineer

Photon

Dallas, TX • On-site

Other

Posted 4 days ago

Job description

Role: Agentic AI Workflow Engineer
Location: Dallas, TX (Onsite)
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/Google Cloud Platform, 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.

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