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Large Language Model Llm Jobs in Arizona (NOW HIRING)

Exposure to LLM (Large Language Models), agentic architectures, and prompt engineering concepts. * Familiarity with ADK (Agent Development Kit), Playbook, or similar agentic frameworks. * Conceptual ...

Test Automation Engineer

Phoenix, AZ · On-site

$76K - $90K/yr

Hands-on experience with Large Language Models (LLMs) * Practical experience with Generative AI * Playwright Automation * Model Context Protocol (MCP) * BDD Frameworks * TestNG * TestX * Java * API ...

Senior Java Backend Developer - GenAI

Phoenix, AZ · On-site

$119K - $155K/yr

... Technologies, and LLM-powered application development. This role focuses on designing and ... Develop AI-powered backend services using Large Language Models (LLMs).Build and optimize Retrieval ...

Java AI Developer

Phoenix, AZ · On-site

$50.25 - $65/hr

... LLM-powered application development. * This role focuses on designing and delivering secure ... Develop AI-powered backend services using Large Language Models (LLMs). * Build and optimize ...

Data Analyst

Phoenix, AZ · On-site

$100K - $110K/yr

... Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI technologies. Working within a highly regulated financial environment, you will contribute to building scalable data ...

Experience with artificial intelligence/large language model platform features, including Skills, Model Context Protocol (MCP), Plugins, or partner-led delivery models involving systems integrators ...

... Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI technologies. Working within a highly regulated financial environment, you will contribute to building scalable data ...

Apply modern artificial intelligence and machine learning techniques, including large language models (LLMs), generative AI, and advanced analytics, to automate processes, enhance decision-making ...

... Troon's data consumable by large language models * Establish technical patterns for AI ... Deep understanding of LLM application architecture, including RAG, function calling, and agent ...

... Troon's data consumable by large language models * Establish technical patterns for AI ... Deep understanding of LLM application architecture, including RAG, function calling, and agent ...

Additionally, experience in integrating with large language models (LLMs) for effective summarization is essential. Key Responsibilities: * Design and develop machine learning algorithms for time ...

Showing results 41-60

Large Language Model Llm information

What are some common challenges faced by large language model llm engineers in their day-to-day work?

LLM Engineers often encounter challenges related to scaling models efficiently, optimizing performance on large and complex datasets, and ensuring the responsible use of AI technologies. Balancing the trade-offs between model accuracy, speed, and ethical considerations can be demanding, especially as real-world applications often require rapid iterations and rigorous testing. Additionally, staying updated with the latest research advancements and integrating new methods into production systems is an ongoing responsibility. Many engineers tackle these challenges by working closely with data scientists, researchers, and product teams in collaborative, agile environments.

What is a large language model llm?

A Large Language Model (LLM) job typically involves working with advanced AI models designed to understand and generate human-like text. Roles in this field may include research, data engineering, model fine-tuning, prompt engineering, or application development. Professionals in LLM jobs often work with machine learning algorithms, natural language processing (NLP), and large-scale datasets to enhance AI capabilities. These roles are common in AI-driven industries, including tech companies, research institutions, and startups. Strong programming skills, knowledge of deep learning frameworks, and expertise in NLP are often required.

What are the key skills and qualifications needed to thrive in the large language model llm position?

Excelling in the role of a Large Language Model (LLM) Engineer requires strong expertise in natural language processing, machine learning, and computer programming, often supported by an advanced degree in computer science or a related field. Familiarity with industry-standard frameworks like PyTorch or TensorFlow, as well as experience with cloud computing platforms and large-scale data management, is highly valued. Communication, creativity, and problem-solving are essential soft skills to effectively collaborate with cross-functional teams and innovate solutions. These skills ensure the development, deployment, and refinement of powerful language models that can address diverse business needs and technical challenges.

What jobs can I do with a large language model?

A large language model can be used in roles such as AI content developer, chatbot designer, or natural language processing specialist. These jobs involve tasks like training, fine-tuning models, creating AI-driven applications, and improving language understanding, often requiring skills in programming, data analysis, and machine learning tools.

What are the most commonly searched types of Large Language Model Llm jobs in Arizona?

The most popular types of Large Language Model Llm jobs in Arizona are:

What are popular job titles related to Large Language Model Llm jobs in Arizona?

For Large Language Model Llm jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Large Language Model Llm jobs in Arizona look for?

The top searched job categories for Large Language Model Llm jobs in Arizona are:

Infographic showing various Large Language Model Llm job openings in Arizona as of August 2026, with employment types broken down into 63% Full Time, 7% Part Time, and 30% Contract. Highlights an 75% In-person, 5% Hybrid, and 20% Remote job distribution.

Senior React / Next.js Engineer (Contract to Hire) - Remote Hybrid - Arizona or SO. California Resid

e360

Phoenix, AZ • On-site, Remote

$90 - $100/hr

Contractor

Posted 20 days ago


Job description

Rate: $90 - $100/ Hour - Depending on Experience
Note: MUST be a US Citizen or Green Card Holder
***NO RECRUITING AGENCIES***
***NO C2C***
***NO Sponsorship available***
About e360's App Engineering
e360 is a 30+ year privately-owned company with a focus on our people, our clients and leading technologies. e360's Cloud Services Division is a rapidly growing business helping clients manage their Cloud technology. Our team is comprised of leaders that focus on delivering innovative consulting solutions that leverage leading and emerging technologies.
We are a dynamic and entrepreneurial consulting company that offers ample opportunities for professional development and growth suited to each individual's personal and professional goals. We offer internal, and subsidize external, trainings, and reimburse the cost of technology certification exams and / or renewals. Our family-founded business sees work life fit as a core value that all of our practitioners practice - the value you add to your team is more important than the time that you 'clock in and out.' You will have numerous opportunities to interface with senior leadership, and benefit from mentorship internally or through introductions through external networks to support your growth.
Description
The Senior React / Next.js Engineer is a hands-on consultant responsible for designing and delivering scalable enterprise web applications.
This role requires advanced experience with React, Next.js, TypeScript, API integration, and modular application architecture. The engineer will also support Intelligent Document Processing solutions and should understand how Python, AI, and Large Language Models can be used in document workflows.
What You'll Do
Design, build, test, and deploy enterprise applications using React, Next.js, and TypeScript.
Create modular, reusable, and maintainable application architectures.
Build shared components, hooks, services, utilities, and design-system patterns.
Design scalable approaches for routing, state management, data fetching, forms, validation, and error handling.
Integrate applications with APIs, authentication systems, enterprise data sources, and document-processing services.
Build document upload, review, correction, approval, and exception-management experiences.
Use Python to support document ingestion, extraction, validation, transformation, and integration.
Apply AI and LLM capabilities to document classification, extraction, summarization, and validation where appropriate.
Improve existing codebases by reducing duplication, tight coupling, inconsistent patterns, and technical debt.
Implement automated testing, CI/CD, logging, monitoring, security, and performance practices.
Own technical workstreams and provide design reviews, code reviews, and mentoring.
Participate in client discovery, requirements analysis, demonstrations, deployment, and knowledge transfer.
Requirements
Advanced experience with React, Next.js, TypeScript, and modern JavaScript.
Strong understanding of React composition, hooks, rendering, and component design.
Experience with Next.js App Router, server and client components, route handlers, middleware, and server-side rendering.
Demonstrated ability to design modular enterprise applications with clear separation of concerns.
Experience building reusable component libraries and working with design systems.
Experience integrating REST APIs, backend services, and third-party platforms.
Experience with state-management and data-fetching tools such as Redux Toolkit, Zustand, TanStack Query, or similar technologies.
Experience building complex forms, validation workflows, and data-review interfaces.
Experience with authentication and authorization using OAuth, OpenID Connect, JWTs, sessions, or role-based access.
Working experience with Python for APIs, automation, data processing, or document workflows.
Experience with Git, automated testing, CI/CD, and production deployment.
Ability to evaluate tradeoffs involving maintainability, performance, scalability, security, and delivery speed. Intelligent Document Processing and AI Bachelor's degree from an accredited college or university
Candidates should have practical experience with or an understanding of:
OCR, document classification, field and table extraction
Structured and unstructured document processing
Confidence scoring, validation rules, and human review
Document status tracking, exception handling, and audit history
Python-based document ingestion, preprocessing, parsing, and transformation
Calling document intelligence, OCR, and AI services from Python
Large Language Models and their use in document extraction, classification, summarization, and validation
Prompt design, structured model outputs, and hallucination risks
The differences between OCR, trained document models, and LLM-based extraction
Data privacy, accuracy, latency, cost, and human-in-the-loop considerations
Deep AI or data-science experience is not required.
Preferred Qualifications
Experience leading enterprise React or Next.js projects.
Experience modernizing or refactoring large frontend codebases.
Experience with document-management, case-management, or workflow applications.
Experience with Azure AI Document Intelligence, Amazon Textract, or comparable services.
Experience with Azure OpenAI, Amazon Bedrock, or other hosted LLM services.
Experience with FastAPI, Flask, Node.js, or backend API development.
Experience with AWS or Azure application hosting and integration services.
Cloud experience is helpful but is not the primary focus of the role.
Professional Skills
Strong application-design and problem-solving skills.
Ability to translate business requirements into practical software designs.
Strong consulting, communication, documentation, and code-review skills.
Ability to independently own technical workstreams.
Ability to identify architectural risks, technical debt, and delivery blockers.
Ability to mentor developers and establish consistent engineering practices.
Critical Success Factors
Ability to independently deliver production-ready React and Next.js applications.
Strong understanding of modular enterprise application architecture.
Ability to create reusable patterns without unnecessary complexity.
Ability to integrate Intelligent Document Processing into enterprise applications.
Practical understanding of Python, AI, and LLM-supported document workflows.
Commitment to code quality, testing, accessibility, security, performance, and maintainability.